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<item rdf:about="http://www.citeulike.org/user/zpinhead/article/1230104">
    <title>Exploiting Social Annotation for Automatic Resource Discovery</title>
    <link>http://www.citeulike.org/user/zpinhead/article/1230104</link>
    <description>&lt;i&gt;(12 Apr 2007)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Information integration applications, such as mediators or mashups, that require access to information resources currently rely on users manually discovering and integrating them in the application. Manual resource discovery is a slow process, requiring the user to sift through results obtained via keyword-based search. Although search methods have advanced to include evidence from document contents, its metadata and the contents and link structure of the referring pages, they still do not adequately cover information sources -- often called &#8220;the hidden Web&#8221;-- that dynamically generate documents in response to a query. The recently popular social bookmarking sites, which allow users to annotate and share metadata about various information sources, provide rich evidence for resource discovery. In this paper, we describe a probabilistic model of the user annotation process in a social bookmarking system del.icio.us. We then use the model to automatically find resources relevant to a particular information domain. Our experimental results on data obtained from <em>del.icio.us</em> show this approach as a promising method for helping automate the resource discovery task.</description>
    <dc:title>Exploiting Social Annotation for Automatic Resource Discovery</dc:title>

    <dc:creator>Anon Plangprasopchok</dc:creator>
    <dc:creator>Kristina Lerman</dc:creator>
    <dc:source>(12 Apr 2007)</dc:source>
    <dc:date>2007-04-16T15:15:35-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:category>annotation</prism:category>
    <prism:category>automatic</prism:category>
    <prism:category>discovery</prism:category>
    <prism:category>resource</prism:category>
    <prism:category>social</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ZiqiZhang/article/1222371">
    <title>Term Extraction + Term Clustering: An Integrated Platform for Computer-Aided Terminology</title>
    <link>http://www.citeulike.org/user/ZiqiZhang/article/1222371</link>
    <description>&lt;i&gt;(1999)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;A novel technique for automatic thesaurus construction is proposed. It is based on the complementary use of two tools: (1) a Term Extraction tool that acquires term candidates from tagged corpora through a shallow grammar of noun phrases, and (2) a Term Clustering tool that groups syntactic variants (insertions). Experiments performed on corpora in three technical domains yield clusters of term candidates with precision rates between 93% and 98%. In Proccedings, 9th Conference of...</description>
    <dc:title>Term Extraction + Term Clustering: An Integrated Platform for Computer-Aided Terminology</dc:title>

    <dc:creator>D Bourigault</dc:creator>
    <dc:creator>C Jacquemin</dc:creator>
    <dc:source>(1999)</dc:source>
    <dc:date>2007-04-12T14:45:48-00:00</dc:date>
    <prism:publicationYear>1999</prism:publicationYear>
    <prism:category>automatic</prism:category>
    <prism:category>recognition</prism:category>
    <prism:category>term</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ZiqiZhang/article/1222367">
    <title>Study and Implementation of Combined Techniques for Automatic Extraction of Terminology</title>
    <link>http://www.citeulike.org/user/ZiqiZhang/article/1222367</link>
    <description>&lt;i&gt;(1996), pp. 49-66.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;This paper presents an original method and its implementation to extract terminology from corpora by combining linguistic filters and statistical methods. Starting from a linguistic study of the terms of telecommunication domain, we designed a number of filters which enable us to obtain a first selection of sequences that may be considered as terms. Various statistical scores are applied to this selection and results are evaluated. This method has been applied to French and to English, but this ...</description>
    <dc:title>Study and Implementation of Combined Techniques for Automatic Extraction of Terminology</dc:title>

    <dc:creator>B&#233;atrice Daille</dc:creator>
    <dc:source>(1996), pp. 49-66.</dc:source>
    <dc:date>2007-04-12T14:43:35-00:00</dc:date>
    <prism:publicationYear>1996</prism:publicationYear>
    <prism:startingPage>49</prism:startingPage>
    <prism:endingPage>66</prism:endingPage>
    <prism:publisher>The MIT Press</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>recognition</prism:category>
    <prism:category>term</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ZiqiZhang/article/1222865">
    <title>Identifying Terms by their Family and Friends</title>
    <link>http://www.citeulike.org/user/ZiqiZhang/article/1222865</link>
    <description>&lt;i&gt;&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Multi-word terms are traditionally identified using statistical techniques or, more recently, using hybrid techniques combining statistics with shallow linguistic information. Approaches to word sense disambiguation and machine translation have taken advantage of contextual information in a more meaningful way, but terminology has rarely followed suit. We present an approach to term recognition which identifies salient parts of the context and measures their strength of association to relevant...</description>
    <dc:title>Identifying Terms by their Family and Friends</dc:title>

    <dc:creator>Diana Maynard</dc:creator>
    <dc:creator>Sophia Ananiadou</dc:creator>
    <dc:date>2007-04-12T20:28:18-00:00</dc:date>
    <prism:category>automatic</prism:category>
    <prism:category>recognition</prism:category>
    <prism:category>term</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ZiqiZhang/article/1158255">
    <title>Methods of automatic term recognition: a review</title>
    <link>http://www.citeulike.org/user/ZiqiZhang/article/1158255</link>
    <description>&lt;i&gt;Terminology, Vol. 3, No. 2. (1996), pp. 259-289.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Following the growing interest in &#34;corpus-based&#34; approaches to computational linguistics, a number of studies have recently appeared on the topic of automatic term recognition or extraction. Because a successful term recognition method has to be based on proper insights into the nature of terms, studies of automatic term recognition not only contribute to the applications of computational linguistics but also to the theoretical foundation of terminology. Many studies on automatic term...</description>
    <dc:title>Methods of automatic term recognition: a review</dc:title>

    <dc:creator>Kyo Kageura</dc:creator>
    <dc:creator>Bin Umino</dc:creator>
    <dc:source>Terminology, Vol. 3, No. 2. (1996), pp. 259-289.</dc:source>
    <dc:date>2007-03-13T13:26:32-00:00</dc:date>
    <prism:publicationYear>1996</prism:publicationYear>
    <prism:publicationName>Terminology</prism:publicationName>
    <prism:volume>3</prism:volume>
    <prism:number>2</prism:number>
    <prism:startingPage>259</prism:startingPage>
    <prism:endingPage>289</prism:endingPage>
    <prism:category>automatic</prism:category>
    <prism:category>recognition</prism:category>
    <prism:category>term</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ZiqiZhang/article/1220947">
    <title>Term Extraction and Automatic Indexing</title>
    <link>http://www.citeulike.org/user/ZiqiZhang/article/1220947</link>
    <description>&lt;i&gt;(2000)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;This chapter presents a new domain of research and development in Natural Language Processing (NLP) that is concerned with the representation, acquisition, and recognition of terms. Terms are pervasive in scientific and technical documents; their identification is a crucial issue for any application dealing with the analysis, understanding, generation, or translation of such documents. In particular, the ever-growing mass of specialized documentation available on-line, in industrial and...</description>
    <dc:title>Term Extraction and Automatic Indexing</dc:title>

    <dc:creator>C Jacquemin</dc:creator>
    <dc:creator>D Et</dc:creator>
    <dc:source>(2000)</dc:source>
    <dc:date>2007-04-11T15:56:38-00:00</dc:date>
    <prism:publicationYear>2000</prism:publicationYear>
    <prism:category>automatic</prism:category>
    <prism:category>recognition</prism:category>
    <prism:category>term</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ZiqiZhang/article/1220927">
    <title>Identification of relevant terms to support the construction of Domain</title>
    <link>http://www.citeulike.org/user/ZiqiZhang/article/1220927</link>
    <description>&lt;i&gt;&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Though the utility of domain Ontologies is now widely acknowledged in the IT (Information Technology) community, several barriers must be overcome before Ontologies become practical and useful tools. One important achievement would be to reduce the cost of identifying and manually entering several thousand-concept descriptions. This paper describes a text mining technique to aid an Ontology Engineer to identify the important concepts in a Domain Ontology.</description>
    <dc:title>Identification of relevant terms to support the construction of Domain</dc:title>

    <dc:creator>Ontologies Velardi</dc:creator>
    <dc:date>2007-04-11T15:48:48-00:00</dc:date>
    <prism:category>automatic</prism:category>
    <prism:category>recognition</prism:category>
    <prism:category>term</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ZiqiZhang/article/1220899">
    <title>Towards automatic extraction of monolingual and bilingual terminology</title>
    <link>http://www.citeulike.org/user/ZiqiZhang/article/1220899</link>
    <description>&lt;i&gt;(1994)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;In this paper, we make use of linguistic knowledge to identify certain noun phrases, both in English and French, which are likely to be terms. We then test and compare ent statistical scores to select the &#34;good&#34; ones among the candidate terms, and finally propose a statistical method to build correspondences of multi-words units across bmguages.</description>
    <dc:title>Towards automatic extraction of monolingual and bilingual terminology</dc:title>

    <dc:creator>B Daille</dc:creator>
    <dc:creator>E Gaussier</dc:creator>
    <dc:creator>J Lange</dc:creator>
    <dc:source>(1994)</dc:source>
    <dc:date>2007-04-11T15:21:11-00:00</dc:date>
    <prism:publicationYear>1994</prism:publicationYear>
    <prism:category>automatic</prism:category>
    <prism:category>recognition</prism:category>
    <prism:category>term</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ville/article/300425">
    <title>Automatic text indexing using complex identifiers</title>
    <link>http://www.citeulike.org/user/ville/article/300425</link>
    <description>&lt;i&gt;(1988), pp. 135-144.&lt;/i&gt;</description>
    <dc:title>Automatic text indexing using complex identifiers</dc:title>

    <dc:creator>Gerald Salton</dc:creator>
    <dc:identifier>doi:10.1145/62506.62530</dc:identifier>
    <dc:source>(1988), pp. 135-144.</dc:source>
    <dc:date>2005-08-22T15:39:17-00:00</dc:date>
    <prism:publicationYear>1988</prism:publicationYear>
    <prism:startingPage>135</prism:startingPage>
    <prism:endingPage>144</prism:endingPage>
    <prism:publisher>ACM Press</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>indexing</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ville/article/300416">
    <title>Automatic concept extraction from spoken medical reports</title>
    <link>http://www.citeulike.org/user/ville/article/300416</link>
    <description>&lt;i&gt;International Journal of Medical Informatics, Vol. 70, No. 2-3. (July 2003), pp. 255-263.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Objective: The objective of this project is to investigate methods whereby a combination of speech recognition and automated indexing methods substitute for current transcription and indexing practices. Methods: We based our study on existing speech recognition software programs and on , a tool that extracts MeSH concepts from medical text in natural language and that is mainly based on a French medical lexicon and on the UMLS. For each document, the process consists of three steps: (1) dictation and digital audio recording, (2) speech recognition, (3) automatic indexing. The evaluation consisted of a comparison between the set of concepts extracted by after the speech recognition phase and the set of keywords manually extracted from the initial document. The method was evaluated on a set of 28 patient discharge summaries extracted from the MENELAS corpus in French, corresponding to in-patients admitted for coronarography. Results: The overall precision was 73% and the overall recall was 90%. Indexing errors were mainly due to word sense ambiguity and abbreviations. A specific issue was the fact that the standard French translation of MeSH terms lacks diacritics. A preliminary evaluation of speech recognition tools showed that the rate of accurate recognition was higher than 98%. Only 3% of the indexing errors were generated by inadequate speech recognition. Discussion: We discuss several areas to focus on to improve this prototype. However, the very low rate of indexing errors due to speech recognition errors highlights the potential benefits of combining speech recognition techniques and automatic indexing.</description>
    <dc:title>Automatic concept extraction from spoken medical reports</dc:title>

    <dc:creator>Andre Happe</dc:creator>
    <dc:creator>Bruno Pouliquen</dc:creator>
    <dc:creator>Anita Burgun</dc:creator>
    <dc:creator>Marc Cuggia</dc:creator>
    <dc:creator>Pierre Le Beux</dc:creator>
    <dc:identifier>doi:10.1016/S1386-5056(03)00055-8</dc:identifier>
    <dc:source>International Journal of Medical Informatics, Vol. 70, No. 2-3. (July 2003), pp. 255-263.</dc:source>
    <dc:date>2005-08-22T15:21:42-00:00</dc:date>
    <prism:publicationYear>2003</prism:publicationYear>
    <prism:publicationName>International Journal of Medical Informatics</prism:publicationName>
    <prism:volume>70</prism:volume>
    <prism:number>2-3</prism:number>
    <prism:startingPage>255</prism:startingPage>
    <prism:endingPage>263</prism:endingPage>
    <prism:category>automatic</prism:category>
    <prism:category>indexing</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ville/article/300408">
    <title>Automated MeSH indexing of the World-Wide Web.</title>
    <link>http://www.citeulike.org/user/ville/article/300408</link>
    <description>&lt;i&gt;Proc Annu Symp Comput Appl Med Care (1995), pp. 893-897.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;To facilitate networked discovery and information retrieval in the biomedical domain, we have designed a system for automatic assignment of Medical Subject Headings to documents retrieved from the World-Wide Web. Our prototype implementations show significant promise. We describe our methods and discuss the further development of a completely automated indexing tool called the &#34;Web-MeSH Medibot.&#34;</description>
    <dc:title>Automated MeSH indexing of the World-Wide Web.</dc:title>

    <dc:creator>J Fowler</dc:creator>
    <dc:creator>S Maram</dc:creator>
    <dc:creator>V Kouramajian</dc:creator>
    <dc:creator>V Devadhar</dc:creator>
    <dc:source>Proc Annu Symp Comput Appl Med Care (1995), pp. 893-897.</dc:source>
    <dc:date>2005-08-22T15:11:14-00:00</dc:date>
    <prism:publicationYear>1995</prism:publicationYear>
    <prism:publicationName>Proc Annu Symp Comput Appl Med Care</prism:publicationName>
    <prism:issn>0195-4210</prism:issn>
    <prism:startingPage>893</prism:startingPage>
    <prism:endingPage>897</prism:endingPage>
    <prism:category>automatic</prism:category>
    <prism:category>indexing</prism:category>
    <prism:category>mesh</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ville/article/293153">
    <title>A blueprint for automatic indexing</title>
    <link>http://www.citeulike.org/user/ville/article/293153</link>
    <description>&lt;i&gt;SIGIR Forum, Vol. 31, No. 1. (1997), pp. 23-36.&lt;/i&gt;</description>
    <dc:title>A blueprint for automatic indexing</dc:title>

    <dc:creator>G Salton</dc:creator>
    <dc:identifier>doi:10.1145/263868.263871</dc:identifier>
    <dc:source>SIGIR Forum, Vol. 31, No. 1. (1997), pp. 23-36.</dc:source>
    <dc:date>2005-08-16T12:52:36-00:00</dc:date>
    <prism:publicationYear>1997</prism:publicationYear>
    <prism:publicationName>SIGIR Forum</prism:publicationName>
    <prism:issn>0163-5840</prism:issn>
    <prism:volume>31</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>23</prism:startingPage>
    <prism:endingPage>36</prism:endingPage>
    <prism:publisher>ACM Press</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>indexing</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ville/article/261435">
    <title>A hierarchical approach to the automatic categorization of medical documents</title>
    <link>http://www.citeulike.org/user/ville/article/261435</link>
    <description>&lt;i&gt;(1998), pp. 132-139.&lt;/i&gt;</description>
    <dc:title>A hierarchical approach to the automatic categorization of medical documents</dc:title>

    <dc:creator>Luciano de Lima</dc:creator>
    <dc:creator>Alberto Laender</dc:creator>
    <dc:creator>Berthier Ribeiro-Neto</dc:creator>
    <dc:identifier>doi:10.1145/288627.288649</dc:identifier>
    <dc:source>(1998), pp. 132-139.</dc:source>
    <dc:date>2005-07-21T10:59:56-00:00</dc:date>
    <prism:publicationYear>1998</prism:publicationYear>
    <prism:startingPage>132</prism:startingPage>
    <prism:endingPage>139</prism:endingPage>
    <prism:publisher>ACM Press</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>mesh</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ville/article/240553">
    <title>WRAPIN: new generation health search engine using UMLS knowledge sources for MeSH term extraction from health documentation.</title>
    <link>http://www.citeulike.org/user/ville/article/240553</link>
    <description>&lt;i&gt;Medinfo, Vol. 11, No. Pt 1. (2004), pp. 356-360.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;To realize the potential of the Internet as a source of valuable healthcare information, for the general public, patients or practitioners, it is imperative to establish a validation system based on standards of quality. The WRAPIN project (World-wide online Reliable Advice to Patients and Individuals) from the European Community has this ambitious goal. WRAPIN is a federating system for medical information with an editorial policy of intelligently sharing quality and professional information. The WRAPIN project has two main axes: the efficient and intelligent search of information and the assertion of the trustworthiness of content. This article presents the scientific challenges involved in extracting the knowledge from text-based information in order to better manage the knowledge and the rest of the retrieval proc-ess. Our innovative approach is to efficiently extract MeSH terms from the analyzed documents exploiting UMLS knowledge sources. A benefit has been measured when comparing extraction results. Even if the evaluation is made with a limited corpus, this research work proposes heuristics that can be validated to the whole biomedical domain, and possibly enhanced by the adjunction of other methods.</description>
    <dc:title>WRAPIN: new generation health search engine using UMLS knowledge sources for MeSH term extraction from health documentation.</dc:title>

    <dc:creator>A Gaudinat</dc:creator>
    <dc:creator>M Joubert</dc:creator>
    <dc:creator>S Aymard</dc:creator>
    <dc:creator>L Falco</dc:creator>
    <dc:creator>C Boyer</dc:creator>
    <dc:creator>M Fieschi</dc:creator>
    <dc:source>Medinfo, Vol. 11, No. Pt 1. (2004), pp. 356-360.</dc:source>
    <dc:date>2005-06-30T06:52:10-00:00</dc:date>
    <prism:publicationYear>2004</prism:publicationYear>
    <prism:publicationName>Medinfo</prism:publicationName>
    <prism:issn>1569-6332</prism:issn>
    <prism:volume>11</prism:volume>
    <prism:number>Pt 1</prism:number>
    <prism:startingPage>356</prism:startingPage>
    <prism:endingPage>360</prism:endingPage>
    <prism:category>automatic</prism:category>
    <prism:category>mesh</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ville/article/270749">
    <title>Automatic Indexing Based on Term Activities</title>
    <link>http://www.citeulike.org/user/ville/article/270749</link>
    <description>&lt;i&gt;Lecture Notes in Computer Science, Vol. 2417 (January 2002), 609.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt; This paper proposes an &#60;SPAN style='background:silver;'&#62;automatic&#60;/SPAN&#62; &#60;SPAN style='background:silver;'&#62;indexing&#60;/SPAN&#62; method named PAI (Priming Activation &#60;SPAN style='background:silver;'&#62;Indexing&#60;/SPAN&#62;) that extracts keywords expressing the author's main point from a document. The basic idea is that since the author writes a document emphasizing his/her main point, impressive terms born in the mind of the reader could represent the asserted keywords. Our approach employs a spreading activation model.</description>
    <dc:title>Automatic Indexing Based on Term Activities</dc:title>

    <dc:creator>Naohiro Matsumura</dc:creator>
    <dc:creator>Yukio Ohsawa</dc:creator>
    <dc:creator>Mitsuru Ishizuka</dc:creator>
    <dc:source>Lecture Notes in Computer Science, Vol. 2417 (January 2002), 609.</dc:source>
    <dc:date>2005-08-01T12:12:13-00:00</dc:date>
    <prism:publicationYear>2002</prism:publicationYear>
    <prism:publicationName>Lecture Notes in Computer Science</prism:publicationName>
    <prism:volume>2417</prism:volume>
    <prism:startingPage>609</prism:startingPage>
    <prism:category>automatic</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ville/article/270732">
    <title>A vector space model for automatic indexing</title>
    <link>http://www.citeulike.org/user/ville/article/270732</link>
    <description>&lt;i&gt;Commun. ACM, Vol. 18, No. 11. (November 1975), pp. 613-620.&lt;/i&gt;</description>
    <dc:title>A vector space model for automatic indexing</dc:title>

    <dc:creator>G Salton</dc:creator>
    <dc:creator>A Wong</dc:creator>
    <dc:creator>CS Yang</dc:creator>
    <dc:identifier>doi:10.1145/361219.361220</dc:identifier>
    <dc:source>Commun. ACM, Vol. 18, No. 11. (November 1975), pp. 613-620.</dc:source>
    <dc:date>2005-08-01T11:57:21-00:00</dc:date>
    <prism:publicationYear>1975</prism:publicationYear>
    <prism:publicationName>Commun. ACM</prism:publicationName>
    <prism:issn>0001-0782</prism:issn>
    <prism:volume>18</prism:volume>
    <prism:number>11</prism:number>
    <prism:startingPage>613</prism:startingPage>
    <prism:endingPage>620</prism:endingPage>
    <prism:publisher>ACM Press</prism:publisher>
    <prism:category>automatic</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ville/article/300470">
    <title>Automatic indexing of online health resources for a French quality controlled gateway</title>
    <link>http://www.citeulike.org/user/ville/article/300470</link>
    <description>&lt;i&gt;Information Processing &#38; Management, Vol. In Press, Corrected Proof&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The profusion of online resources calls for tools and methods to help Internet users find precisely what they are looking for. Quality controlled gateway CISMeF provides such services for health resources. However, the human cost of maintaining and updating the catalogue are increasingly high. This paper presents the automatic indexing system currently developed in the CISMeF team to be used as such for preliminary indexing, or after human reviewing for the final indexing. The system architecture, using the INTEX platform for MeSH term extraction is detailed. The results of a first evaluation tend to indicate that the automatic indexing strategy is relevant, as it achieves a precision comparable to that of other existing operational systems. Moreover, the system presented in this paper retrieves keyword/qualifier pairs as opposed to single terms, therefore providing a significantly more precise indexing. Further development and tests will be carried out in order to improve the coverage of the dictionaries, and validate the efficiency of the system in the indexers' everyday work.</description>
    <dc:title>Automatic indexing of online health resources for a French quality controlled gateway</dc:title>

    <dc:creator>Aurelie Neveol</dc:creator>
    <dc:creator>Alexandrina Rogozan</dc:creator>
    <dc:creator>Stefan Darmoni</dc:creator>
    <dc:identifier>doi:10.1016/j.ipm.2005.01.003</dc:identifier>
    <dc:source>Information Processing &#38; Management, Vol. In Press, Corrected Proof</dc:source>
    <dc:date>2005-08-22T16:51:50-00:00</dc:date>
    <prism:publicationName>Information Processing &#38; Management</prism:publicationName>
    <prism:volume>In Press, Corrected Proof</prism:volume>
    <prism:category>automatic</prism:category>
    <prism:category>mesh</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ville/article/256629">
    <title>Developing practical automatic metadata assignment and evaluation tools for internet resources</title>
    <link>http://www.citeulike.org/user/ville/article/256629</link>
    <description>&lt;i&gt;(2005), pp. 291-300.&lt;/i&gt;</description>
    <dc:title>Developing practical automatic metadata assignment and evaluation tools for internet resources</dc:title>

    <dc:creator>Gordon Paynter</dc:creator>
    <dc:identifier>doi:10.1145/1065385.1065454</dc:identifier>
    <dc:source>(2005), pp. 291-300.</dc:source>
    <dc:date>2005-07-15T11:21:22-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:startingPage>291</prism:startingPage>
    <prism:endingPage>300</prism:endingPage>
    <prism:publisher>ACM Press</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>keyphrase</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ville/article/300427">
    <title>Syntactic approaches to automatic book indexing</title>
    <link>http://www.citeulike.org/user/ville/article/300427</link>
    <description>&lt;i&gt;(1988), pp. 204-210.&lt;/i&gt;</description>
    <dc:title>Syntactic approaches to automatic book indexing</dc:title>

    <dc:creator>Gerard Salton</dc:creator>
    <dc:source>(1988), pp. 204-210.</dc:source>
    <dc:date>2005-08-22T15:43:43-00:00</dc:date>
    <prism:publicationYear>1988</prism:publicationYear>
    <prism:startingPage>204</prism:startingPage>
    <prism:endingPage>210</prism:endingPage>
    <prism:publisher>Association for Computational Linguistics</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>indexing</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ville/article/264842">
    <title>An experimental study in auomatically categorizing medical documents</title>
    <link>http://www.citeulike.org/user/ville/article/264842</link>
    <description>&lt;i&gt;J. Am. Soc. Inf. Sci. Technol., Vol. 52, No. 5. (March 2001), pp. 391-401.&lt;/i&gt;</description>
    <dc:title>An experimental study in auomatically categorizing medical documents</dc:title>

    <dc:creator>Berthier Ribeiro-Neto</dc:creator>
    <dc:creator>Alberto Laender</dc:creator>
    <dc:creator>Luciano de Lima</dc:creator>
    <dc:identifier>doi:10.1002/1532-2890(2001)9999:9999&#60;::AID-ASI1083&#62;3.3.CO;2-T</dc:identifier>
    <dc:source>J. Am. Soc. Inf. Sci. Technol., Vol. 52, No. 5. (March 2001), pp. 391-401.</dc:source>
    <dc:date>2005-07-26T05:10:16-00:00</dc:date>
    <prism:publicationYear>2001</prism:publicationYear>
    <prism:publicationName>J. Am. Soc. Inf. Sci. Technol.</prism:publicationName>
    <prism:issn>1532-2882</prism:issn>
    <prism:volume>52</prism:volume>
    <prism:number>5</prism:number>
    <prism:startingPage>391</prism:startingPage>
    <prism:endingPage>401</prism:endingPage>
    <prism:publisher>John Wiley &#38; Sons, Inc.</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>mesh</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ville/article/303205">
    <title>Automatic MeSH term assignment and quality assessment.</title>
    <link>http://www.citeulike.org/user/ville/article/303205</link>
    <description>&lt;i&gt;Proc AMIA Symp (2001), pp. 319-323.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;For computational purposes documents or other objects are most often represented by a collection of individual attributes that may be strings or numbers. Such attributes are often called features and success in solving a given problem can depend critically on the nature of the features selected to represent documents. Feature selection has received considerable attention in the machine learning literature. In the area of document retrieval we refer to feature selection as indexing. Indexing has not traditionally been evaluated by the same methods used in machine learning feature selection. Here we show how indexing quality may be evaluated in a machine learning setting and apply this methodology to results of the Indexing Initiative at the National Library of Medicine.</description>
    <dc:title>Automatic MeSH term assignment and quality assessment.</dc:title>

    <dc:creator>W Kim</dc:creator>
    <dc:creator>AR Aronson</dc:creator>
    <dc:creator>WJ Wilbur</dc:creator>
    <dc:source>Proc AMIA Symp (2001), pp. 319-323.</dc:source>
    <dc:date>2005-08-25T09:14:19-00:00</dc:date>
    <prism:publicationYear>2001</prism:publicationYear>
    <prism:publicationName>Proc AMIA Symp</prism:publicationName>
    <prism:issn>1531-605X</prism:issn>
    <prism:startingPage>319</prism:startingPage>
    <prism:endingPage>323</prism:endingPage>
    <prism:category>automatic</prism:category>
    <prism:category>mesh</prism:category>
    <prism:category>nlm</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/tulaydemir/article/1766076">
    <title>Automating the extraction of data from HTML tables with unknown structure</title>
    <link>http://www.citeulike.org/user/tulaydemir/article/1766076</link>
    <description>&lt;i&gt;Data Knowl. Eng., Vol. 54, No. 1. (July 2005), pp. 3-28.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Data on the Web in HTML tables is mostly structured, but we usually do not know the structure in advance. Thus, we cannot directly query for data of interest. We propose a solution to this problem based on document-independent extraction ontologies. Our solution entails elements of table understanding, data integration, and wrapper creation. Table understanding allows us to find tables of interest within a Web page, recognize attributes and values within the table, pair attributes with values, and form records. Data-integration techniques allow us to match source records with a target schema. Ontologically specified wrappers allow us to extract data from source records into a target schema. Experimental results show that we can successfully locate data of interest in tables and map the data from source HTML tables with unknown structure to a given target database schema. We can thus “directly” query source data with unknown structure through a known target schema.</description>
    <dc:title>Automating the extraction of data from HTML tables with unknown structure</dc:title>

    <dc:creator>David Embley</dc:creator>
    <dc:creator>Cui Tao</dc:creator>
    <dc:creator>Stephen Liddle</dc:creator>
    <dc:identifier>doi:10.1016/j.datak.2004.10.004</dc:identifier>
    <dc:source>Data Knowl. Eng., Vol. 54, No. 1. (July 2005), pp. 3-28.</dc:source>
    <dc:date>2007-10-14T02:40:17-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Data Knowl. Eng.</prism:publicationName>
    <prism:volume>54</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>3</prism:startingPage>
    <prism:endingPage>28</prism:endingPage>
    <prism:publisher>Elsevier Science Publishers B. V.</prism:publisher>
    <prism:category>2005</prism:category>
    <prism:category>automatic</prism:category>
    <prism:category>extraction</prism:category>
    <prism:category>ontology</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/tulaydemir/article/494446">
    <title>Extracting structured data from Web pages</title>
    <link>http://www.citeulike.org/user/tulaydemir/article/494446</link>
    <description>&lt;i&gt;(2003), pp. 337-348.&lt;/i&gt;</description>
    <dc:title>Extracting structured data from Web pages</dc:title>

    <dc:creator>Arvind Arasu</dc:creator>
    <dc:creator>Hector Garcia-Molina</dc:creator>
    <dc:creator>Stanford University</dc:creator>
    <dc:identifier>doi:10.1145/872757.872799</dc:identifier>
    <dc:source>(2003), pp. 337-348.</dc:source>
    <dc:date>2006-02-06T21:35:14-00:00</dc:date>
    <prism:publicationYear>2003</prism:publicationYear>
    <prism:startingPage>337</prism:startingPage>
    <prism:endingPage>348</prism:endingPage>
    <prism:publisher>ACM Press</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>creation</prism:category>
    <prism:category>extract</prism:category>
    <prism:category>model</prism:category>
    <prism:category>page</prism:category>
    <prism:category>template</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/tulaydemir/article/1179337">
    <title>Automatic extraction of dynamic record sections from search engine result pages</title>
    <link>http://www.citeulike.org/user/tulaydemir/article/1179337</link>
    <description>&lt;i&gt;(2006), pp. 989-1000.&lt;/i&gt;</description>
    <dc:title>Automatic extraction of dynamic record sections from search engine result pages</dc:title>

    <dc:creator>Hongkun Zhao</dc:creator>
    <dc:creator>Weiyi Meng</dc:creator>
    <dc:creator>Clement Yu</dc:creator>
    <dc:identifier>doi:10.1145/872757.872799</dc:identifier>
    <dc:source>(2006), pp. 989-1000.</dc:source>
    <dc:date>2007-03-21T15:21:02-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:startingPage>989</prism:startingPage>
    <prism:endingPage>1000</prism:endingPage>
    <prism:publisher>VLDB Endowment</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>record_extraction</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/tulaydemir/article/494100">
    <title>Automatic information extraction from semi-structured Web pages by pattern discovery</title>
    <link>http://www.citeulike.org/user/tulaydemir/article/494100</link>
    <description>&lt;i&gt;Decis. Support Syst., Vol. 35, No. 1. (April 2003), pp. 129-147.&lt;/i&gt;</description>
    <dc:title>Automatic information extraction from semi-structured Web pages by pattern discovery</dc:title>

    <dc:creator>Chia-Hui Chang</dc:creator>
    <dc:creator>Chun-Nan Hsu</dc:creator>
    <dc:creator>Shao-Cheng Lui</dc:creator>
    <dc:identifier>doi:10.1016/S0167-9236(02)00100-8</dc:identifier>
    <dc:source>Decis. Support Syst., Vol. 35, No. 1. (April 2003), pp. 129-147.</dc:source>
    <dc:date>2006-02-06T07:31:53-00:00</dc:date>
    <prism:publicationYear>2003</prism:publicationYear>
    <prism:publicationName>Decis. Support Syst.</prism:publicationName>
    <prism:issn>0167-9236</prism:issn>
    <prism:volume>35</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>129</prism:startingPage>
    <prism:endingPage>147</prism:endingPage>
    <prism:publisher>Elsevier Science Publishers B. V.</prism:publisher>
    <prism:category>2003</prism:category>
    <prism:category>automatic</prism:category>
    <prism:category>extraction</prism:category>
    <prism:category>iepad</prism:category>
    <prism:category>pattern</prism:category>
    <prism:category>semi-structured</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/tulaydemir/article/530795">
    <title>Automatic Web Information Extraction in the ROADRUNNER System</title>
    <link>http://www.citeulike.org/user/tulaydemir/article/530795</link>
    <description>&lt;i&gt;(2002), pp. 264-277.&lt;/i&gt;</description>
    <dc:title>Automatic Web Information Extraction in the ROADRUNNER System</dc:title>

    <dc:creator>Valter Crescenzi</dc:creator>
    <dc:creator>Giansalvatore Mecca</dc:creator>
    <dc:creator>Paolo Merialdo</dc:creator>
    <dc:source>(2002), pp. 264-277.</dc:source>
    <dc:date>2006-03-04T06:08:15-00:00</dc:date>
    <prism:publicationYear>2002</prism:publicationYear>
    <prism:startingPage>264</prism:startingPage>
    <prism:endingPage>277</prism:endingPage>
    <prism:publisher>Springer-Verlag</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>extraction</prism:category>
    <prism:category>html</prism:category>
    <prism:category>roadrunner</prism:category>
    <prism:category>system</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ss363/article/2501486">
    <title>Highly Dynamic Adaptation in Process Management Systems Through Execution Monitoring</title>
    <link>http://www.citeulike.org/user/ss363/article/2501486</link>
    <description>&lt;i&gt;Business Process Management (2007), pp. 182-197.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Nowadays, process management systems can be used not only in classical business scenarios, but also in highly mobile and dynamic situations, e.g., in supporting operators during emergency management in order to coordinate their activities. In such challenging situations, processes should be adapted, in order to cope with anomalous situations, including connection anomalies and task faults. In this paper, we present a general approach, based on execution monitoring, which is (i) practical, by relying on well-established planning techniques, and (ii) does not require the definition of the adaptation strategy in the process itself (as most of the current approaches do). We prove the correctness and completeness of the approach.</description>
    <dc:title>Highly Dynamic Adaptation in Process Management Systems Through Execution Monitoring</dc:title>

    <dc:creator>Massimiliano de Leoni</dc:creator>
    <dc:creator>Massimo Mecella</dc:creator>
    <dc:creator>Giuseppe De Giacomo</dc:creator>
    <dc:identifier>doi:10.1007/978-3-540-75183-0_14</dc:identifier>
    <dc:source>Business Process Management (2007), pp. 182-197.</dc:source>
    <dc:date>2008-03-10T16:01:59-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>Business Process Management</prism:publicationName>
    <prism:startingPage>182</prism:startingPage>
    <prism:endingPage>197</prism:endingPage>
    <prism:category>adaptation</prism:category>
    <prism:category>automatic</prism:category>
    <prism:category>dynamic</prism:category>
    <prism:category>execution</prism:category>
    <prism:category>for</prism:category>
    <prism:category>in</prism:category>
    <prism:category>monitoring</prism:category>
    <prism:category>process</prism:category>
    <prism:category>scenarios</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/sjgaller/article/2738650">
    <title>A specification-based fitness function for evolutionary testing of object-oriented programs</title>
    <link>http://www.citeulike.org/user/sjgaller/article/2738650</link>
    <description>&lt;i&gt;(2006), pp. 1953-1954.&lt;/i&gt;</description>
    <dc:title>A specification-based fitness function for evolutionary testing of object-oriented programs</dc:title>

    <dc:creator>Yoonsik Cheon</dc:creator>
    <dc:creator>Myoung Kim</dc:creator>
    <dc:identifier>doi:10.1145/1143997.1144322</dc:identifier>
    <dc:source>(2006), pp. 1953-1954.</dc:source>
    <dc:date>2008-04-30T13:44:32-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:startingPage>1953</prism:startingPage>
    <prism:endingPage>1954</prism:endingPage>
    <prism:publisher>ACM</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>java</prism:category>
    <prism:category>jml</prism:category>
    <prism:category>softnet</prism:category>
    <prism:category>testing</prism:category>
    <prism:category>unit-testing</prism:category>
    <prism:category>unit-tests</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/sjgaller/article/2738590">
    <title>Reconciling Manual and Automated Testing: The AutoTest Experience</title>
    <link>http://www.citeulike.org/user/sjgaller/article/2738590</link>
    <description>&lt;i&gt;(2007)&lt;/i&gt;</description>
    <dc:title>Reconciling Manual and Automated Testing: The AutoTest Experience</dc:title>

    <dc:creator>Andreas Leitner</dc:creator>
    <dc:creator>Ilinca Ciupa</dc:creator>
    <dc:creator>Bertrand Meyer</dc:creator>
    <dc:creator>Mark Howard</dc:creator>
    <dc:identifier>doi:10.1109/HICSS.2007.462</dc:identifier>
    <dc:source>(2007)</dc:source>
    <dc:date>2008-04-30T13:24:09-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publisher>IEEE Computer Society</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>autotest</prism:category>
    <prism:category>eiffel</prism:category>
    <prism:category>softnet</prism:category>
    <prism:category>testing</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/sjgaller/article/1673808">
    <title>Anzu: A Tool for Property Synthesis</title>
    <link>http://www.citeulike.org/user/sjgaller/article/1673808</link>
    <description>&lt;i&gt;Computer Aided Verification (2007), pp. 258-262.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;We present the tool Anzu. Anzu takes a formal specification of a design and generates a functionally correct system if one exists. The specification is given as a set of linear temporal logic (LTL) formulas belonging to the class of generalized reactivity of rank 1. Such formulas cover the majority of the formulas used in practice. Anzu is an implementation of the symbolic reactive(1) approach to synthesis by Piterman, Pnueli, and Sa’ar. If the specification is realizable Anzu provides the user with a Verilog module that represents a correct finite-state system.</description>
    <dc:title>Anzu: A Tool for Property Synthesis</dc:title>

    <dc:creator>Barbara Jobstmann</dc:creator>
    <dc:creator>Stefan Galler</dc:creator>
    <dc:creator>Martin Weiglhofer</dc:creator>
    <dc:creator>Roderick Bloem</dc:creator>
    <dc:identifier>doi:10.1007/978-3-540-73368-3_29</dc:identifier>
    <dc:source>Computer Aided Verification (2007), pp. 258-262.</dc:source>
    <dc:date>2007-09-19T05:43:08-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>Computer Aided Verification</prism:publicationName>
    <prism:startingPage>258</prism:startingPage>
    <prism:endingPage>262</prism:endingPage>
    <prism:category>automatic</prism:category>
    <prism:category>case-study</prism:category>
    <prism:category>specification</prism:category>
    <prism:category>synthesis</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/sjgaller/article/2215249">
    <title>Automatic Testing of Object-Oriented Software</title>
    <link>http://www.citeulike.org/user/sjgaller/article/2215249</link>
    <description>&lt;i&gt;SOFSEM 2007: Theory and Practice of Computer Science (2007), pp. 114-129.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Effective testing involves preparing test oracles and test cases, two activities which are too tedious to be effectively performed by humans, yet for the most part remain manual. The AutoTest unit testing framework automates both, by using Eiffel contracts — already present in the software — as test oracles, and generating objects and routine arguments to exercise all given classes; manual tests can also be added, and all failed test cases are automatically retained for regression testing, in a “minimized” form retaining only the relevant instructions. AutoTest has already detected numerous hitherto unknown bugs in production software.</description>
    <dc:title>Automatic Testing of Object-Oriented Software</dc:title>

    <dc:creator>Bertrand Meyer</dc:creator>
    <dc:creator>Ilinca Ciupa</dc:creator>
    <dc:creator>Andreas Leitner</dc:creator>
    <dc:creator>Lisa Liu</dc:creator>
    <dc:identifier>doi:10.1007/978-3-540-69507-3_9</dc:identifier>
    <dc:source>SOFSEM 2007: Theory and Practice of Computer Science (2007), pp. 114-129.</dc:source>
    <dc:date>2008-01-10T16:18:46-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>SOFSEM 2007: Theory and Practice of Computer Science</prism:publicationName>
    <prism:startingPage>114</prism:startingPage>
    <prism:endingPage>129</prism:endingPage>
    <prism:category>automatic</prism:category>
    <prism:category>eiffel</prism:category>
    <prism:category>softnet</prism:category>
    <prism:category>testing</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/sjgaller/article/2341632">
    <title>Specify, Compile, Run: Hardware from PSL</title>
    <link>http://www.citeulike.org/user/sjgaller/article/2341632</link>
    <description>&lt;i&gt;Electron. Notes Theor. Comput. Sci., Vol. 190, No. 4. (November 2007), pp. 3-16.&lt;/i&gt;</description>
    <dc:title>Specify, Compile, Run: Hardware from PSL</dc:title>

    <dc:creator>Roderick Bloem</dc:creator>
    <dc:creator>Stefan Galler</dc:creator>
    <dc:creator>Barbara Jobstmann</dc:creator>
    <dc:creator>Nir Piterman</dc:creator>
    <dc:creator>Amir Pnueli</dc:creator>
    <dc:creator>Martin Weiglhofer</dc:creator>
    <dc:identifier>doi:10.1016/j.entcs.2007.09.004</dc:identifier>
    <dc:source>Electron. Notes Theor. Comput. Sci., Vol. 190, No. 4. (November 2007), pp. 3-16.</dc:source>
    <dc:date>2008-02-06T13:38:01-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:publicationName>Electron. Notes Theor. Comput. Sci.</prism:publicationName>
    <prism:issn>1571-0661</prism:issn>
    <prism:volume>190</prism:volume>
    <prism:number>4</prism:number>
    <prism:startingPage>3</prism:startingPage>
    <prism:endingPage>16</prism:endingPage>
    <prism:publisher>Elsevier Science Publishers B. V.</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>case-study</prism:category>
    <prism:category>specification</prism:category>
    <prism:category>synthesis</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/sjgaller/article/1421838">
    <title>Interactive presentation: Automatic hardware synthesis from specifications: a case study</title>
    <link>http://www.citeulike.org/user/sjgaller/article/1421838</link>
    <description>&lt;i&gt;(2007), pp. 1188-1193.&lt;/i&gt;</description>
    <dc:title>Interactive presentation: Automatic hardware synthesis from specifications: a case study</dc:title>

    <dc:creator>Roderick Bloem</dc:creator>
    <dc:creator>Stefan Galler</dc:creator>
    <dc:creator>Barbara Jobstmann</dc:creator>
    <dc:creator>Nir Piterman</dc:creator>
    <dc:creator>Amir Pnueli</dc:creator>
    <dc:creator>Martin Weiglhofer</dc:creator>
    <dc:identifier>doi:10.1145/1266366.1266622</dc:identifier>
    <dc:source>(2007), pp. 1188-1193.</dc:source>
    <dc:date>2007-06-29T08:52:21-00:00</dc:date>
    <prism:publicationYear>2007</prism:publicationYear>
    <prism:startingPage>1188</prism:startingPage>
    <prism:endingPage>1193</prism:endingPage>
    <prism:publisher>ACM Press</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>case-study</prism:category>
    <prism:category>specification</prism:category>
    <prism:category>synthesis</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/seungwon/article/911932">
    <title>Automatic categorization of figures in scientific documents</title>
    <link>http://www.citeulike.org/user/seungwon/article/911932</link>
    <description>&lt;i&gt;(2006), pp. 129-138.&lt;/i&gt;</description>
    <dc:title>Automatic categorization of figures in scientific documents</dc:title>

    <dc:creator>Xiaonan Lu</dc:creator>
    <dc:creator>Prasenjit Mitra</dc:creator>
    <dc:creator>James Wang</dc:creator>
    <dc:creator>Lee Giles</dc:creator>
    <dc:identifier>doi:10.1145/1141753.1141778</dc:identifier>
    <dc:source>(2006), pp. 129-138.</dc:source>
    <dc:date>2006-10-24T20:09:48-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:startingPage>129</prism:startingPage>
    <prism:endingPage>138</prism:endingPage>
    <prism:publisher>ACM Press</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>categorization</prism:category>
    <prism:category>image</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/seungwon/article/920697">
    <title>A hierarchical, HMM-based automatic evaluation of OCR accuracy for a digital library of books</title>
    <link>http://www.citeulike.org/user/seungwon/article/920697</link>
    <description>&lt;i&gt;(2006), pp. 109-118.&lt;/i&gt;</description>
    <dc:title>A hierarchical, HMM-based automatic evaluation of OCR accuracy for a digital library of books</dc:title>

    <dc:creator>Shaolei Feng</dc:creator>
    <dc:creator>R Manmatha</dc:creator>
    <dc:identifier>doi:10.1145/1141753.1141776</dc:identifier>
    <dc:source>(2006), pp. 109-118.</dc:source>
    <dc:date>2006-10-31T18:02:01-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:startingPage>109</prism:startingPage>
    <prism:endingPage>118</prism:endingPage>
    <prism:publisher>ACM Press</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>evaluation</prism:category>
    <prism:category>hmm</prism:category>
    <prism:category>ocr</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/seb314/article/2398239">
    <title>Automatic Class Selection and Prototyping for 3-D Object Classification</title>
    <link>http://www.citeulike.org/user/seb314/article/2398239</link>
    <description>&lt;i&gt;(2005), pp. 64-71.&lt;/i&gt;</description>
    <dc:title>Automatic Class Selection and Prototyping for 3-D Object Classification</dc:title>

    <dc:creator>Raghavendra Donamukkala</dc:creator>
    <dc:creator>Daniel Huber</dc:creator>
    <dc:creator>Anuj Kapuria</dc:creator>
    <dc:creator>Martial Hebert</dc:creator>
    <dc:identifier>doi:10.1109/3DIM.2005.22</dc:identifier>
    <dc:source>(2005), pp. 64-71.</dc:source>
    <dc:date>2008-02-19T11:39:41-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:startingPage>64</prism:startingPage>
    <prism:endingPage>71</prism:endingPage>
    <prism:publisher>IEEE Computer Society</prism:publisher>
    <prism:category>3d</prism:category>
    <prism:category>automatic</prism:category>
    <prism:category>classification</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/scis0000001/article/878832">
    <title>Automatic Conjecture Making in Mathematics</title>
    <link>http://www.citeulike.org/user/scis0000001/article/878832</link>
    <description>&lt;i&gt;&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;JCAI-87 and has been a member of the IJCAI Inc. Trustees. (The biennial IJCAIs are the major conferences in AI). He was general chair of CADE-12 (The biennial CADEs are the major conferences in automated theorem proving) and has been President of the CADE Inc. Board of Trustees. In 1986 he received the SPL Insight Award for his contribution to artificial intelligence research. He was elected a founding Fellow of AAAI in 1990, a fellow of the Royal Society of Edinburgh in 1996 and a founding...</description>
    <dc:title>Automatic Conjecture Making in Mathematics</dc:title>

    <dc:creator>Simon Colton</dc:creator>
    <dc:creator>Alan Bundy</dc:creator>
    <dc:creator>Toby Walsh</dc:creator>
    <dc:date>2006-09-30T12:40:52-00:00</dc:date>
    <prism:category>automatic</prism:category>
    <prism:category>conjecture</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/scis0000001/article/891137">
    <title>A topology-shape-metrics approach for the automatic layout of UML class diagrams</title>
    <link>http://www.citeulike.org/user/scis0000001/article/891137</link>
    <description>&lt;i&gt;(2003), pp. 189-ff.&lt;/i&gt;</description>
    <dc:title>A topology-shape-metrics approach for the automatic layout of UML class diagrams</dc:title>

    <dc:creator>Markus Eiglsperger</dc:creator>
    <dc:creator>Michael Kaufmann</dc:creator>
    <dc:creator>Martin Siebenhaller</dc:creator>
    <dc:identifier>doi:10.1145/774833.774860</dc:identifier>
    <dc:source>(2003), pp. 189-ff.</dc:source>
    <dc:date>2006-10-10T09:09:36-00:00</dc:date>
    <prism:publicationYear>2003</prism:publicationYear>
    <prism:startingPage>189</prism:startingPage>
    <prism:endingPage>ff</prism:endingPage>
    <prism:publisher>ACM Press</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>diagram</prism:category>
    <prism:category>layout</prism:category>
    <prism:category>uml</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/scis0000001/article/1050962">
    <title>Multimodal Reasoning for Automatic Model Construction</title>
    <link>http://www.citeulike.org/user/scis0000001/article/1050962</link>
    <description>&lt;i&gt;(1998), pp. 181-188.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;This paper describes a program called Pret that automates system identication, the process of nding a dynamical model of a black-box system. Pret performs both structural identication and parameter estimation by integrating several reasoning modes: qualitative reasoning, qualitative simulation, numerical simulation, geometric reasoning, constraint reasoning, resolution, reasoning with abstraction levels, declarative meta-level control, and a simple form of truth maintenance. Unlike ...</description>
    <dc:title>Multimodal Reasoning for Automatic Model Construction</dc:title>

    <dc:creator>Reinhard Stolle</dc:creator>
    <dc:creator>Elizabeth Bradley</dc:creator>
    <dc:source>(1998), pp. 181-188.</dc:source>
    <dc:date>2007-01-19T10:25:57-00:00</dc:date>
    <prism:publicationYear>1998</prism:publicationYear>
    <prism:startingPage>181</prism:startingPage>
    <prism:endingPage>188</prism:endingPage>
    <prism:category>automatic</prism:category>
    <prism:category>inference</prism:category>
    <prism:category>modeling</prism:category>
    <prism:category>multimodal</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/scis0000001/article/1216046">
    <title>Formal design principles of a complete automatic database design procedure system for “syntactic” database management systems</title>
    <link>http://www.citeulike.org/user/scis0000001/article/1216046</link>
    <description>&lt;i&gt;Cybernetics and Systems Analysis, Vol. 23, No. 3. (1 May 1987), pp. 377-383.&lt;/i&gt;</description>
    <dc:title>Formal design principles of a complete automatic database design procedure system for “syntactic” database management systems</dc:title>

    <dc:creator>OM Veinerov</dc:creator>
    <dc:creator>VM Blyum</dc:creator>
    <dc:creator>MS Kazarov</dc:creator>
    <dc:identifier>doi:10.1007/BF01074829</dc:identifier>
    <dc:source>Cybernetics and Systems Analysis, Vol. 23, No. 3. (1 May 1987), pp. 377-383.</dc:source>
    <dc:date>2007-04-08T14:42:08-00:00</dc:date>
    <prism:publicationYear>1987</prism:publicationYear>
    <prism:publicationName>Cybernetics and Systems Analysis</prism:publicationName>
    <prism:volume>23</prism:volume>
    <prism:number>3</prism:number>
    <prism:startingPage>377</prism:startingPage>
    <prism:endingPage>383</prism:endingPage>
    <prism:category>automatic</prism:category>
    <prism:category>database</prism:category>
    <prism:category>design</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/scis0000001/article/933413">
    <title>A Graph Model for Unsupervised Lexical Acquisition</title>
    <link>http://www.citeulike.org/user/scis0000001/article/933413</link>
    <description>&lt;i&gt;(August 2002), pp. 1093-1099.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;This paper presents an unsupervised method for assembling semantic knowledge from a part-of-speech tagged corpus using graph algorithms. The graph model is built by linking pairs of words which participate in particular syntactic relationships. We focus on the symmetric relationship between pairs of nouns which occur together in lists. An incremental cluster-building algorithm using this part of the graph achieves 82% accuracy at a lexical acquisition task, evaluated against WordNet classes....</description>
    <dc:title>A Graph Model for Unsupervised Lexical Acquisition</dc:title>

    <dc:creator>Dominic Widdows</dc:creator>
    <dc:creator>Beate Dorow</dc:creator>
    <dc:source>(August 2002), pp. 1093-1099.</dc:source>
    <dc:date>2006-11-06T14:45:02-00:00</dc:date>
    <prism:publicationYear>2002</prism:publicationYear>
    <prism:startingPage>1093</prism:startingPage>
    <prism:endingPage>1099</prism:endingPage>
    <prism:category>automatic</prism:category>
    <prism:category>graph</prism:category>
    <prism:category>lexical-acquisition</prism:category>
    <prism:category>unsupervised</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/rprince/article/2304811">
    <title>Automatic detection of learner’s affect from conversational cues</title>
    <link>http://www.citeulike.org/user/rprince/article/2304811</link>
    <description>&lt;i&gt;User Modeling and User-Adapted Interaction, Vol. 18, No. 1. (25 February 2008), pp. 45-80.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Abstract&#160;&#160;We explored the reliability of detecting a learner’s affect from conversational features extracted from interactions with AutoTutor, an intelligent tutoring system (ITS) that helps students learn by holding a conversation in natural language. Training data were collected in a learning session with AutoTutor, after which the affective states of the learner were rated by the learner, a peer, and two trained judges. Inter-rater reliability scores indicated that the classifications of the trained judges were more reliable than the novice judges. Seven data sets that temporally integrated the affective judgments with the dialogue features of each learner were constructed. The first four datasets corresponded to the judgments of the learner, a peer, and two trained judges, while the remaining three data sets combined judgments of two or more raters. Multiple regression analyses confirmed the hypothesis that dialogue features could significantly predict the affective states of boredom, confusion, flow, and frustration. Machine learning experiments indicated that standard classifiers were moderately successful in discriminating the affective states of boredom, confusion, flow, frustration, and neutral, yielding a peak accuracy of 42% with neutral (chance&#160;=&#160;20%) and 54% without neutral (chance&#160;=&#160;25%). Individual detections of boredom, confusion, flow, and frustration, when contrasted with neutral affect, had maximum accuracies of 69, 68, 71, and 78%, respectively (chance&#160;=&#160;50%). The classifiers that operated on the emotion judgments of the trained judges and combined models outperformed those based on judgments of the novices (i.e., the self and peer). Follow-up classification analyses that assessed the degree to which machine-generated affect labels correlated with affect judgments provided by humans revealed that human-machine agreement was on par with novice judges (self and peer) but quantitatively lower than trained judges. We discuss the prospects of extending AutoTutor into an affect-sensing ITS.</description>
    <dc:title>Automatic detection of learner’s affect from conversational cues</dc:title>

    <dc:creator>Sidney D’mello</dc:creator>
    <dc:creator>Scotty Craig</dc:creator>
    <dc:creator>Amy Witherspoon</dc:creator>
    <dc:creator>Bethany Mcdaniel</dc:creator>
    <dc:creator>Arthur Graesser</dc:creator>
    <dc:identifier>doi:10.1007/s11257-007-9037-6</dc:identifier>
    <dc:source>User Modeling and User-Adapted Interaction, Vol. 18, No. 1. (25 February 2008), pp. 45-80.</dc:source>
    <dc:date>2008-01-29T18:30:47-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>User Modeling and User-Adapted Interaction</prism:publicationName>
    <prism:volume>18</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>45</prism:startingPage>
    <prism:endingPage>80</prism:endingPage>
    <prism:category>affective</prism:category>
    <prism:category>automatic</prism:category>
    <prism:category>conversational</prism:category>
    <prism:category>detection</prism:category>
    <prism:category>learning</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/ranford/article/4487">
    <title>Automatic Meaning Discovery Using Google</title>
    <link>http://www.citeulike.org/user/ranford/article/4487</link>
    <description>&lt;i&gt;(21 December 2004)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;We propose a new method to extract semantic knowledge from the world-wide-web for both supervised and unsupervised learning using the Google search engine in an unconventional manner. The approach is novel in its unrestricted problem domain, simplicity of implementation, and manifestly ontological underpinnings. We give evidence of elementary learning of the semantics of concepts, in contrast to most prior approaches. The method works as follows: The world-wide-web is the largest database on earth, and it induces a probability mass function, the Google distribution, via page counts for combinations of search queries. This distribution allows us to tap the latent semantic knowledge on the web. Shannon's coding theorem is used to establish a code-length associated with each search query. Viewing this mapping as a data compressor, we connect to earlier work on Normalized Compression Distance. We give applications in (i) unsupervised hierarchical clustering, demonstrating the ability to distinguish between colors and numbers, and to distinguish between 17th century Dutch painters; (ii) supervised concept-learning by example, using Support Vector Machines, demonstrating the ability to understand electrical terms, religious terms, emergency incidents, and by conducting a massive experiment in understanding WordNet categories; and (iii) matching of meaning, in an example of automatic English-Spanish translation.</description>
    <dc:title>Automatic Meaning Discovery Using Google</dc:title>

    <dc:creator>Rudi Cilibrasi</dc:creator>
    <dc:creator>Paul Vitanyi</dc:creator>
    <dc:source>(21 December 2004)</dc:source>
    <dc:date>2004-12-22T12:39:20-00:00</dc:date>
    <prism:publicationYear>2004</prism:publicationYear>
    <prism:category>ai</prism:category>
    <prism:category>automatic</prism:category>
    <prism:category>discovery</prism:category>
    <prism:category>distance</prism:category>
    <prism:category>google</prism:category>
    <prism:category>meaning</prism:category>
    <prism:category>normalized</prism:category>
    <prism:category>semantic</prism:category>
    <prism:category>web</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/pichai/article/816102">
    <title>CiteSeer: An Automatic Citation Indexing System</title>
    <link>http://www.citeulike.org/user/pichai/article/816102</link>
    <description>&lt;i&gt;(June FebruaryMarch--FebruaryJune 1998), pp. 89-98.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;We present CiteSeer: an autonomous citation indexing system which indexes academic literature in electronic format (e.g. Postscript files on the Web). CiteSeer understands how to parse citations, identify citations to the same paper in different formats, and identify the context of citations in the body of articles. CiteSeer provides most of the advantages of traditional (manually constructed) citation indexes (e.g. the ISI citation indexes), including: literature retrieval by following...</description>
    <dc:title>CiteSeer: An Automatic Citation Indexing System</dc:title>

    <dc:creator>Lee Giles</dc:creator>
    <dc:creator>Kurt Bollacker</dc:creator>
    <dc:creator>Steve Lawrence</dc:creator>
    <dc:source>(June FebruaryMarch--FebruaryJune 1998), pp. 89-98.</dc:source>
    <dc:date>2006-08-24T22:48:31-00:00</dc:date>
    <prism:publicationYear>1998</prism:publicationYear>
    <prism:startingPage>89</prism:startingPage>
    <prism:endingPage>98</prism:endingPage>
    <prism:publisher>ACM Press</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>citation</prism:category>
    <prism:category>index</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/pcr/article/250108">
    <title>FrontDesk: An Enterprise Class Web-Based Software System for Programming Assignment Submission, Feedback Dissemination, and Grading Automation</title>
    <link>http://www.citeulike.org/user/pcr/article/250108</link>
    <description>&lt;i&gt;(2004), pp. 331-335.&lt;/i&gt;</description>
    <dc:title>FrontDesk: An Enterprise Class Web-Based Software System for Programming Assignment Submission, Feedback Dissemination, and Grading Automation</dc:title>

    <dc:creator>Mike Maxim</dc:creator>
    <dc:creator>Ashish Venugopal</dc:creator>
    <dc:source>(2004), pp. 331-335.</dc:source>
    <dc:date>2005-07-08T18:28:49-00:00</dc:date>
    <prism:publicationYear>2004</prism:publicationYear>
    <prism:startingPage>331</prism:startingPage>
    <prism:endingPage>335</prism:endingPage>
    <prism:publisher>IEEE Computer Society</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>grading</prism:category>
    <prism:category>manual</prism:category>
    <prism:category>rate5</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/nishiokov/article/2983402">
    <title>Role for Subthalamic Nucleus Neurons in Switching from Automatic to Controlled Eye Movement</title>
    <link>http://www.citeulike.org/user/nishiokov/article/2983402</link>
    <description>&lt;i&gt;J. Neurosci., Vol. 28, No. 28. (9 July 2008), pp. 7209-7218.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The subthalamic nucleus (STN) of the basal ganglia is an important element of motor control. This is demonstrated by involuntary movements induced by STN lesions and the successful treatment of Parkinson's disease by STN stimulation. However, it is still unclear how individual STN neurons participate in motor control. Here, we report that the STN has a function in switching from automatic to volitionally controlled eye movement. In the STN of trained macaque monkeys, we found neurons that showed a phasic change in activity specifically before volitionally controlled saccades which were switched from automatic saccades. A majority of switch-related neurons were considered to inhibit no-longer-valid automatic processes, and the inhibition started early enough to enable the animal to switch. We suggest that the STN mediates the control signal originated from the medial frontal cortex and implements the behavioral switching function using its connections with other basal ganglia nuclei and the superior colliculus. 10.1523/JNEUROSCI.0487-08.2008</description>
    <dc:title>Role for Subthalamic Nucleus Neurons in Switching from Automatic to Controlled Eye Movement</dc:title>

    <dc:creator>Masaki Isoda</dc:creator>
    <dc:creator>Okihide Hikosaka</dc:creator>
    <dc:identifier>doi:10.1523/JNEUROSCI.0487-08.2008</dc:identifier>
    <dc:source>J. Neurosci., Vol. 28, No. 28. (9 July 2008), pp. 7209-7218.</dc:source>
    <dc:date>2008-07-10T01:23:17-00:00</dc:date>
    <prism:publicationYear>2008</prism:publicationYear>
    <prism:publicationName>J. Neurosci.</prism:publicationName>
    <prism:volume>28</prism:volume>
    <prism:number>28</prism:number>
    <prism:startingPage>7209</prism:startingPage>
    <prism:endingPage>7218</prism:endingPage>
    <prism:category>automatic</prism:category>
    <prism:category>basal_ganglia</prism:category>
    <prism:category>habit-learning</prism:category>
    <prism:category>monkey</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/mova/article/2389281">
    <title>A FPGA-based architecture for automatic hexagonal bolts detection in railway maintenance</title>
    <link>http://www.citeulike.org/user/mova/article/2389281</link>
    <description>&lt;i&gt;Computer Architecture for Machine Perception, 2005. CAMP 2005. Proceedings. Seventh International Workshop on (2005), pp. 219-224.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Rail inspection is a very important task in railway maintenance and it is periodically needed for preventing dangerous situations. Inspection is operated manually by trained human operator walking along the track searching for visual anomalies. This monitoring is unacceptable for slowness and lack of objectivity, because the results are related to the ability of the observer to recognize critical situations. The paper presents a prototypal FPGA-based architecture which automatically detects presence/absence of the fastening bolts that fix the rails to the sleepers. A simple predicting algorithm, exploiting the geometry of the railways, extracts, from the long video sequence acquired by a digital line scan camera, few windows where the presence of bolts is expected. These windows are preprocessed according to a Haar transform and then provided to a multilayer perceptron neural classifiers (MLPNCs) which reveals the presence/absence of the fastening bolts with an accuracy of 99.6% in detecting visible bolts and of 95% in detecting missing bolts. A FPGA-based architecture performs these tasks in 13.29 /spl mu/s, allowing an on-the-fly analysis of a video sequence acquired up at 190 km/h.</description>
    <dc:title>A FPGA-based architecture for automatic hexagonal bolts detection in railway maintenance</dc:title>

    <dc:creator>G De Ruvo</dc:creator>
    <dc:creator>P De Ruvo</dc:creator>
    <dc:creator>F Marino</dc:creator>
    <dc:creator>G Mastronardi</dc:creator>
    <dc:creator>PL Mazzeo</dc:creator>
    <dc:creator>E Stella</dc:creator>
    <dc:identifier>doi:10.1109/CAMP.2005.4</dc:identifier>
    <dc:source>Computer Architecture for Machine Perception, 2005. CAMP 2005. Proceedings. Seventh International Workshop on (2005), pp. 219-224.</dc:source>
    <dc:date>2008-02-16T23:09:39-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Computer Architecture for Machine Perception, 2005. CAMP 2005. Proceedings. Seventh International Workshop on</prism:publicationName>
    <prism:startingPage>219</prism:startingPage>
    <prism:endingPage>224</prism:endingPage>
    <prism:category>artificial</prism:category>
    <prism:category>automatic</prism:category>
    <prism:category>detection</prism:category>
    <prism:category>fpga</prism:category>
    <prism:category>marino</prism:category>
    <prism:category>poliba</prism:category>
    <prism:category>vision</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/moltean/article/299977">
    <title>Evolving Evolutionary Algorithms Using Linear Genetic Programming</title>
    <link>http://www.citeulike.org/user/moltean/article/299977</link>
    <description>&lt;i&gt;Evolutionary Computation, Vol. 13, No. 3. (September 2005), pp. 387-410.&lt;/i&gt;</description>
    <dc:title>Evolving Evolutionary Algorithms Using Linear Genetic Programming</dc:title>

    <dc:creator>Mihai Oltean</dc:creator>
    <dc:identifier>doi:10.1162/1063656054794815</dc:identifier>
    <dc:source>Evolutionary Computation, Vol. 13, No. 3. (September 2005), pp. 387-410.</dc:source>
    <dc:date>2005-08-21T09:58:30-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Evolutionary Computation</prism:publicationName>
    <prism:issn>1063-6560</prism:issn>
    <prism:volume>13</prism:volume>
    <prism:number>3</prism:number>
    <prism:startingPage>387</prism:startingPage>
    <prism:endingPage>410</prism:endingPage>
    <prism:publisher>MIT Press</prism:publisher>
    <prism:category>algorithms</prism:category>
    <prism:category>automatic</prism:category>
    <prism:category>computer</prism:category>
    <prism:category>evolutionary</prism:category>
    <prism:category>evolving</prism:category>
    <prism:category>generation</prism:category>
    <prism:category>genetic</prism:category>
    <prism:category>gp</prism:category>
    <prism:category>linear</prism:category>
    <prism:category>meta</prism:category>
    <prism:category>of</prism:category>
    <prism:category>programming</prism:category>
    <prism:category>programs</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/mohriner/article/141451">
    <title>A Review of Automatic Rhythm Description Systems</title>
    <link>http://www.citeulike.org/user/mohriner/article/141451</link>
    <description>&lt;i&gt;Computer Music Journal, Vol. 29, No. 1. (February 2005), pp. 34-54.&lt;/i&gt;</description>
    <dc:title>A Review of Automatic Rhythm Description Systems</dc:title>

    <dc:creator>Gouyon Fabien</dc:creator>
    <dc:creator>Dixon Simon</dc:creator>
    <dc:source>Computer Music Journal, Vol. 29, No. 1. (February 2005), pp. 34-54.</dc:source>
    <dc:date>2005-03-26T18:45:39-00:00</dc:date>
    <prism:publicationYear>2005</prism:publicationYear>
    <prism:publicationName>Computer Music Journal</prism:publicationName>
    <prism:issn>0148-9267</prism:issn>
    <prism:volume>29</prism:volume>
    <prism:number>1</prism:number>
    <prism:startingPage>34</prism:startingPage>
    <prism:endingPage>54</prism:endingPage>
    <prism:publisher>MIT Press</prism:publisher>
    <prism:category>automatic</prism:category>
    <prism:category>transcription</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/masaakif/article/2439395">
    <title>Gaussian Mixture Modeling of Short-Time Fourier Transform Features for Audio Fingerprinting</title>
    <link>http://www.citeulike.org/user/masaakif/article/2439395</link>
    <description>&lt;i&gt;IEEE Transactions on Information Forensics and Security, Vol. 1, No. 4. (December 2006), pp. 457-463.&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;In audio fingerprinting, an audio clip must be recognized by matching an extracted fingerprint to a database of previously computed fingerprints. The fingerprints should reduce the dimensionality of the input significantly, provide discrimination among different audio clips, and, at the same time, be invariant to distorted versions of the same audio clip. In this paper, we design fingerprints addressing the above issues by modeling an audio clip by Gaussian mixture models (GMM). We evaluate the performance of many easy-to-compute short-time Fourier transform features, such as Shannon entropy, Renyi entropy, spectral centroid, spectral bandwidth, spectral flatness measure, spectral crest factor, and Mel-frequency cepstral coefficients in modeling audio clips using GMM for fingerprinting. We test the robustness of the fingerprints under a large number of distortions. To make the system robust, we use some of the distorted versions of the audio for training. However, we show that the audio fingerprints modeled using GMM are not only robust to the distortions used in training but also to distortions not used in training. Among the features tested, spectral centroid performs best with an identification rate of 99.2% at a false positive rate of 10&#60;sup&#62;-4&#60;/sup&#62;. All of the features give an identification rate of more than 90% at a false positive rate of 10&#60;sup&#62;-3&#60;/sup&#62;</description>
    <dc:title>Gaussian Mixture Modeling of Short-Time Fourier Transform Features for Audio Fingerprinting</dc:title>

    <dc:creator>Arunan Ramalingam</dc:creator>
    <dc:creator>Sridhar Krishnan</dc:creator>
    <dc:identifier>doi:10.1109/TIFS.2006.885036</dc:identifier>
    <dc:source>IEEE Transactions on Information Forensics and Security, Vol. 1, No. 4. (December 2006), pp. 457-463.</dc:source>
    <dc:date>2008-02-28T02:15:33-00:00</dc:date>
    <prism:publicationYear>2006</prism:publicationYear>
    <prism:publicationName>IEEE Transactions on Information Forensics and Security</prism:publicationName>
    <prism:volume>1</prism:volume>
    <prism:number>4</prism:number>
    <prism:startingPage>457</prism:startingPage>
    <prism:endingPage>463</prism:endingPage>
    <prism:category>analysis</prism:category>
    <prism:category>audio</prism:category>
    <prism:category>automatic</prism:category>
    <prism:category>bandwidth</prism:category>
    <prism:category>centroid</prism:category>
    <prism:category>cepstral</prism:category>
    <prism:category>clip</prism:category>
    <prism:category>coefficient</prism:category>
    <prism:category>crest</prism:category>
    <prism:category>data</prism:category>
    <prism:category>entropy</prism:category>
    <prism:category>extraction</prism:category>
    <prism:category>factor</prism:category>
    <prism:category>feature</prism:category>
    <prism:category>fingerprint</prism:category>
    <prism:category>fingerprinting</prism:category>
    <prism:category>flatness</prism:category>
    <prism:category>fourier</prism:category>
    <prism:category>gaussian</prism:category>
    <prism:category>identification</prism:category>
    <prism:category>measure</prism:category>
    <prism:category>mel-frequency</prism:category>
    <prism:category>mixture</prism:category>
    <prism:category>modeling</prism:category>
    <prism:category>models</prism:category>
    <prism:category>of</prism:category>
    <prism:category>processes</prism:category>
    <prism:category>processing</prism:category>
    <prism:category>renyi</prism:category>
    <prism:category>security</prism:category>
    <prism:category>shannon</prism:category>
    <prism:category>short-time</prism:category>
    <prism:category>signal</prism:category>
    <prism:category>song</prism:category>
    <prism:category>spectral</prism:category>
    <prism:category>transform</prism:category>
    <prism:category>transforms</prism:category>
</item>



</rdf:RDF>

