CiteULike: brightbyte's library [142 articles]

A proposal to automatically build and maintain gazetteers for Named Entity Recognition by using Wikipedia

A Toral — 2008-02-09T14:34:17-00:00

EACL 2006 (2006)

Unsupervised Named-Entity Recognition: Generating Gazetteers and Resolving Ambiguity

David Nadeau — 2007-06-05T23:44:35-00:00

Advances in Artificial Intelligence (2006), pp. 266-277.

In this paper, we propose a named-entity recognition (NER) system that addresses two major limitations frequently discussed in the field. First, the system requires no human intervention such as manually labeling training data or creating gazetteers. Second, the system can handle more than the three classical named-entity types (person, location, and organization). We describe the system’s architecture and compare its performance with a supervised system. We experimentally evaluate the system on a standard corpus, with the three classical named-entity types, and also on a new corpus, with a new named-entity type (car brands).

Automatic Word Sense Discrimination

Hinrich Schutze — 2006-03-31T13:01:11-00:00

Computational Linguistics, Vol. 24, No. 1. (1998), pp. 97-123.

This paper presents context-group discrimination, a disambiguation algorithm based on clustering. Senses are interpreted as groups (or clusters) of similar contexts of the ambiguous word. Words, contexts, and senses are represented in Word Space, a high-dimensional, real-valued space in which closeness corresponds to semantic similarity. Similarity in Word Space is based on second-order co-occurrence: two tokens (or contexts) of the ambiguous word are assigned to the same sense cluster if the...

Using Information Content to Evaluate Semantic Similarity in a Taxonomy

Philip Resnik — 2006-10-01T01:01:30-00:00

(1995), pp. 448-453.

This paper presents a new measure of semantic similarity in an is-a taxonomy, based on the notion of information content. Experimental evaluation suggests that the measure performs encouragingly well (a correlation of r = 0.79 with a benchmark set of human similarity judgments, with an upper bound of r = 0.90 for human subjects performing the same task), and significantly better than the traditional edge counting approach (r = 0.66).

Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project

Douglas Lenat — 2007-10-30T12:10:01-00:00

(05 April 1990)

Automatic construction of a hypernym-labeled noun hierarchy from text

Sharon Caraballo — 2006-03-01T01:53:03-00:00

(1999), pp. 120-126.

Spinning the Semantic Web : Bringing the World Wide Web to Its Full Potential

Tim Berners-Lee — 2006-05-11T02:56:18-00:00

(01 March 2005)

As the World Wide Web continues to expand, it becomes increasingly difficult for users to obtain information efficiently. Because most search engines read format languages such as HTML or SGML, search results reflect formatting tags more than actual page content, which is expressed in natural language. Spinning the Semantic Web describes an exciting new type of hierarchy and standardization that will replace the current "web of links" with a "web of meaning." Using a flexible set of languages and tools, the Semantic Web will make all available information -- display elements, metadata, services, images, and especially content -- accessible. The result will be an immense repository of information accessible for a wide range of new applications. This first handbook for the Semantic Web covers, among other topics, software agents that can negotiate and collect information, markup languages that can tag many more types of information in a document, and knowledge systems that enable machines to read Web pages and determine their reliability. The truly interdisciplinary Semantic Web combines aspects of artificial intelligence, markup languages, natural language processing, information retrieval, knowledge representation, intelligent agents, and databases.

Evaluating WordNet-based Measures of Lexical Semantic Relatedness

Alexander Budanitsky — 2006-03-11T19:30:37-00:00

Computational Linguistics, Vol. 32, No. 1. (March 2006), pp. 13-47.

The Wiki Way: Collaboration and Sharing on the Internet

Bo Leuf — 2005-03-04T21:40:58-00:00

(03 April 2001)

Suitable for system administrators or managers seeking an affordable content-management solution, The Wiki Way shows off how to take advantage of Wiki collaborative software, which allows users to post and edit content remotely. This book is all you need to get up and running with this exciting (and free) way to build and manage content. This text is first and foremost a guide to what Wiki software is and how to install, customize, and administer it within your organization. Early sections discuss the advantages of Wiki Web sites, which allow all users to add and edit content. While it might sound like a free-for-all, the authors suggest such Web sites have been used successfully in research, business, and education to document project designs, for brainstorming, and for otherwise creating content in a collaborative fashion. Case studies for such organizations as Georgia Tech, New York Times Digital, and Motorola give a glimpse of Wiki used in real settings, so you will get a sense of what to expect. This book is also a guide to the nuts and bolts of downloading and installing Wiki and customizing it for your site. Sections on basic tweaks to Wiki's Perl scripts will let you customize your site to match your organization's needs. Standout material includes almost three dozen customization tips. This volume is illustrated with actual screen shots of Wiki, so you can get a sense of what it is like for users to work together in such an unrestricted fashion. Throughout the text, the authors are suitably upbeat about Wiki's prospects for wider adoption, but they are realistic enough to note compromises (such as requiring passwords and restricting edit rights) required in business settings. They also survey the field of Wiki open-source projects and clones, as well as other similar content-management solutions (such as Zope and the emerging WebDAV standard). While it's hard to predict whether Wiki-based Web sites are for everyone, this book presents the pros and cons of a potentially exciting and useful tool that promotes collaborative content creation. This title can help any organization get going with a Wiki Web site, from the standpoint of planning, deployment, and basic administration. --Richard Dragan Topics covered:<ul><li>Collaboration tools explained <li>Web-based collaboration <li>WebDAV <li>Introduction to Wiki <li>User conventions with Wiki <li>Survey of Wiki open-source projects and clones <li>Installing Wiki (including Apache Web Server and security issues) <li>Using Wiki (making notes, Wiki used as a PIM, content management and links, page editing) <li>How to structure Wiki content (suggested default structure: pros and cons) <li>Customizing Wiki <li>Tour of Wiki Perl scripts and tips for customizing your Wiki site <li>Wiki add-ons (including spellchecking and uploading files) <li>Administration in Wiki (viewing events, controlling access and authentication, database administration, and debugging techniques) <li>Guidelines for Wiki projects (dos and don'ts) <li>Wiki case studies for education <li>Business and research</ul>

An effective approach to document retrieval via utilizing wordnet and recognizing phrases

Shuang Liu — 2008-02-09T13:47:58-00:00

(2004)

Knowledge Derived from Wikipedia for Computing Semantic Relatedness

Simone Ponzetto — 2008-02-09T13:43:06-00:00

Journal of Artificial Intelligence Research, Vol. 30 (2007), pp. 181-212.

Wikipedia provides a semantic network for computing semantic relatedness in a more structured fashion than a search engine and with more coverage than WordNet. We present experiments on using Wikipedia for computing semantic relatedness and compare it to WordNet on various benchmarking datasets. Existing relatedness measures perform better using Wikipedia than a baseline given by Google counts, and we show that Wikipedia outperforms WordNet on some datasets. We also address the question whether and how Wikipedia can be integrated into NLP applications as a knowledge base. Including Wikipedia improves the performance of a machine learning based coreference resolution system, indicating that it represents a valuable resource for NLP applications. Finally, we show that our method can be easily used for languages other than English by computing semantic relatedness for a German dataset.

An API for Measuring the Relatedness of Words in Wikipedia

SP Ponzetto — 2008-02-09T13:40:25-00:00

Companion Volume to the Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (2007), pp. 23-30.

Automatically creating datasets for measures of semantic relatedness

Torsten Zesch — 2008-02-08T22:09:17-00:00

(2006), pp. 16-24.

Ontology-based contextual coherence scoring

R Porzel — 2007-05-08T16:39:51-00:00

(2003)

In this paper we present a contextual extension to ONTOSCORE, a system for scoring sets of concepts on the basis of an ontology. We apply the contextually enhanced system to the task of scoring alternative speech recognition hypotheses (SRH) in terms of their semantic coherence.

Network Analysis for Wikipedia

Francesco Bellomi — 2008-02-07T11:08:23-00:00

(2005)

Network analysis is concerned with properties related to connectivity and distances in graphs, with diverse applications like citation indexing and information retrieval on the Web. HITS (Hyperlink-Induced Topic Search) is a network analysis algorithm that has been successfully used for ranking web pages related to a common topic according to their potential relevance. HITS is based on the notions of hub and authority: a good hub is a page that points to several good authorities; a good authority is a page that is pointed at by several good hubs. HITS exclusively relies on the hyperlink relations existing among the pages, to define the two mutually reinforcing measures of hub and authority. It can be proved that for each page these two weights converge to fixed points, the actual hub and authority values for the page. Authority is used to rank pages resulting from a given query (and thus potentially related to a given topic) in order of relevance. The hyperlinked structure of Wikipedia and the ongoing, incremental editing process behind it make it an interesting and unexplored target domain for network analysis techniques. In particular, we explored the relevance of the notion of HITS's authority on this encyclopedic corpus. We've developed a crawler that extensively scans through the structure of English language Wikipedia articles, and that keeps track for each entry of all other Wikipedia articles pointed at in its de¯nition. The result is a directed graph (roughly 500000 nodes, and more than 8 millions links), which consists for the most part of a big loosely connected component. Then we applied the HITS algorithm to the latter, thus getting a hub and authority weight associated to every entry. First results seem to be meaningful in characterizing the notion of authority in this peculiar domain. Highest-rank authorities seem to be for the most part lexical elements that denote particular and concrete rather than universal and abstract entities. More precisely, at the very top of the authority scale there are concepts used to structure space and time like country names, city names and other geopolitical entities (such as United States and many European countries), historical periods and landmark events (World War II, 1960s). "Television", "scientifc classification" and "animal" are the first three most authoritative common nouns. We will also present the first results issued from the application of well-known PageRank algorithm (Google's popular ranking metrics detailed in [2]) to the Wikipedia entries collected by our crawler.

Finding Related Pages Using Green Measures: An Illustration with Wikipedia

Yann Ollivier — 2008-02-07T11:05:54-00:00

(2007)

We introduce a new method for finding nodes semantically related to a given node in a hyperlinked graph: the Green method, based on a classical Markov chain tool. It is generic, adjustment-free and easy to implement. We test it in the case of the hyperlink structure of the English version of Wikipedia, the on-line encyclopedia. We present an extensive comparative study of the performance of our method versus several other classical methods in the case of Wikipedia. The Green method is found to have both the best average results and the best robustness.

Lexical authorities in an encyclopedic corpus: a case study with wikipedia

F Bellomi — 2008-02-07T11:01:40-00:00

(2005)

Clustering short texts using wikipedia

Somnath Banerjee — 2007-07-28T23:52:16-00:00

(2007), pp. 787-788.

Analyzing and Accessing Wikipedia as a Lexical Semantic Resource

Torsten Zesch — 2008-02-07T10:48:31-00:00

(2007)

We analyze Wikipedia as a lexical semantic resource and compare it with conventional resources, such as dictionaries, thesauri, semantic wordnets, etc. Different parts of Wikipedia reflect different aspects of these resources. We show that Wikipedia contains a vast amount of knowledge about, e.g., named entities, domain specific terms, and rare word senses. If Wikipedia is to be used as a lexical semantic resource in large-scale NLP tasks, efficient programmatic access to the knowledge therein is required. We review existing access mechanisms and show that they are limited with respect to performance and the provided access functions. Therefore, we introduce a general purpose, high performance Java-based Wikipedia API that overcomes these limitations. It is available for research purposes at http://www.ukp.tu-darmstadt.de/software/WikipediaAPI.

Comparing Wikipedia and German Wordnet by Evaluating Semantic Relatedness on Multiple Datasets

Torsten Zesch — 2008-02-07T10:42:47-00:00

(2007)

We evaluate semantic relatedness mea- sures on different German datasets show- ing that their performance depends on: (i) the deﬁnition of relatedness that was underlying the construction of the evaluation dataset, and (ii) the knowledge source used for computing semantic relatedness. We analyze how the underlying knowledge source inﬂuences the performance of a measure. Finally, we investigate the combination of wordnets and Wikipedia to improve the performance of semantic re- latedness measures.

Analysis of the Wikipedia Category Graph for NLP Applications

Torsten Zesch — 2008-02-07T10:38:15-00:00

(2007)

In this paper, we discuss two graphs in Wikipedia (i) the article graph, and (ii) the category graph. We perform a graph-theoretic analysis of the category graph, and show that it is a scale-free, small world graph like other well-known lexical semantic networks. We substantiate our ﬁndings by transferring semantic relatedness algorithms deﬁned on WordNet to the Wikipedia category graph. To assess the usefulness of the category graph as an NLP resource, we analyze its coverage and the performance of the transferred semantic relatedness algorithms.

Boosting Inductive Transfer for Text Classification Using Wikipedia

Somnath Banerjee — 2008-02-07T10:17:42-00:00

(2007), pp. 148-153.

Improving multilingual catalog search services by means of multilingual thesaurus disambiguation

Nogueras Iso — 2008-02-01T21:10:39-00:00

10th European Commission GI&GIS Workshop, ESDI: The State of the Art, Warsaw, Poland (2004)

Multilinguality is an important aspect for the creation of public services in countries like Spain, with four official languages (Spanish, Catalonian, Basque and Galician), and overall, if these services are aimed for a European audience with a big number of official languages. Thus, an initiative for creating a catalog service at the Spanish or at the European level must take into account the necessity of supporting metadata written in a variety of languages. When a user submits a query request to a catalog, (s)he should obtain the data resources that verify the restriction specified by the user and with independence of the language used in the metadata records describing these resources. Our R&D group has developed a strategy for managing these multilingual metadata aspects that face up the problem from three points of view: the use of multilingual controlled lists, the use of multilingual and interrelated thesauri, and the word sense disambiguation of large text descriptive elements. These three substrategies, integrated within a catalog server, are being currently tested in several spatial data infrastructure projects.

SKOS: Simple Knowledge Organisation for the Web

Alistair Miles — 2007-12-17T22:45:59-00:00

This article introduces the Simple Knowledge Organisation System (SKOS), a Semantic Web language for representing controlled structured vocabularies, including thesauri, classification schemes, subject heading systems, and taxonomies. SKOS provides a framework for publishing thesauri, classification schemes, and subject indexes on the Web, and for applying these systems to resource collections that are part of the Semantic Web. Semantic Web applications may harvest and merge SKOS data, to integrate and enhance retrieval service across multiple collections (e.g., libraries). This article also describes some alternatives for integrating Semantic Web services based on the Resource Description Framework (RDF) and SKOS into a distributed enterprise architecture. doi:10.1300/J104v43n03_05

A Method to Convert Thesauri to SKOS

Mark van Assem — 2007-06-08T16:05:37-00:00

The Semantic Web: Research and Applications (2006), pp. 95-109.

Thesauri can be useful resources for indexing and retrieval on the Semantic Web, but often they are not published in RDF/OWL. To convert thesauri to RDF for use in Semantic Web applications and to ensure the quality and utility of the conversion a structured method is required. Moreover, if different thesauri are to be interoperable without complicated mappings, a standard schema for thesauri is required. This paper presents a method for conversion of thesauri to the SKOS RDF/OWL schema, which is a proposal for such a standard under development by W3C’s Semantic Web Best Practices Working Group. We apply the method to three thesauri: IPSV, GTAA and MeSH. With these case studies we evaluate our method and the applicability of SKOS for representing thesauri.

A Theory of Retrieval Using Structured Vocabularies

Alistair Miles — 2008-01-27T21:40:40-00:00

(2006)

A primary motivation for the development of the Semantic Web has been the need for effective information retrieval systems which may be realised through vocabulary control and the use of structured metadata. The technological framework of the Web (URI, HTTP, XML) and of the Semantic Web (RDF, OWL, SPARQL) provides a platform upon which distributed data and metadata applications may be constructed, but does not in itself provide any direct support for information retrieval applications per se. Widely applicable Semantic Web languages that extend this basic layer and provide generic support for retrieval applications, in addition to good practice guidelines and design patterns for developing such applications, are required. The ultimate purpose of this report is to develop a formal theory of retrieval using controlled vocabularies that have a simple and intuitive structure, to provide the necessary theoretical foundations for the development of Semantic Web languages and design patterns for distributed retrieval applications. The main body of this report is devoted to the articulation of such a theory. The theory is expressed formally through the use of mathematical notation, with the intention that this level of formality will provide the bridge between informal requirements specifications and the implementation of effective retrieval applications in computer systems. Specifically, a theory is developed to describe the ways in which a structured vocabulary may be used to construct an index over a collection of objects and then used to express queries which may be evaluated against an index to obtain a set of results. This theory is extended to consider ways in which both the precision and recall of retrieval strategies may be improved, through the use of expansion and ranking techniques and through “coordination”. The problem of translating between controlled vocabularies is also considered. The theory attempts to formalise, unify and extend the traditional wisdom of the library sciences regarding the use of thesauri, classification schemes, subject heading systems, taxonomies and other types of structured vocabulary, so that proven techniques and methodologies may be transferred to a Semantic Web context. The recently chartered W3C Semantic Web Deployment Working Group has been charged with the development of the Simple Knowledge Organisation System (SKOS) to W3C Recommendation status. SKOS is a Semantic Web language specifically intended to support information retrieval applications using controlled vocabularies that have a relatively simple structure. A formal requirements specification is the first planned deliverable in the standardisation of SKOS. An immediate goal of this report is to provide a level of abstraction that can be used to perform a comparative analysis of use cases involving information retrieval systems that operate with structured vocabularies, so that the requirements of these systems with respect to Semantic Web languages such as SKOS may be clearly determined. Also, this report suggests ways in which the theory may be mapped to concrete language constructs and representation patterns in Semantic Web languages. In so doing it is hoped that the development of SKOS and similar languages may be grounded with sufficient rigour to ensure their wide applicability and consistent use.

The Wiki Way of Knowledge Management with Topic Maps.

Tobias Redmann — 2008-01-21T13:47:21-00:00

(2007), pp. 352-357.

Qualitätsaspekte der Wikipedia

Rainer Hammwöhner — 2008-01-20T21:30:13-00:00

Kommunikation@gesellschaft, No. B3. (2007)

Eine kritische Diskussion über ihre Verlässlichkeit begleitet die Entwicklung der Wikipedia von Beginn an. Mittlerweile liegen einige Publikationen vor, die sich mit der Qualität dieser neuen Enzyklopädie befassen. In diesem Betrag wird ein kurzer Überblick über mehrere dieser Arbeiten gegeben. Anschließend werden zwei eigene Studien vorgestellt, die sich mit Qualitätsaspekten befassen, die bisher weniger berücksichtigt wurden. In der ersten Studie wird die Abdeckung eines gut umgrenzten Themenkomplexes – Shakespeare’s Werk – in mehreren Wikipedias untersucht. Die zweite Studie befasst sich mit der Qualität der Wissensorganisation in der Wikipedia.

Deriving a large scale taxonomy from wikipedia

Simone Ponzetto — 2008-01-02T12:21:48-00:00

SemTag and Seeker: Bootstrapping the Semantic Web via Automated Semantic Annotation

S Dill — 2006-10-14T04:55:50-00:00

(2003)

This paper describes Seeker, a platform for large-scale text analytics, and SemTag, an application written on the platform to perform automated semantic tagging of large corpora. We apply SemTag to a collection of approximately 264 million web pages, and generate approximately 434 million automatically disambiguated semantic tags, published to the web as a label bureau providing metadata regarding the 434 million annotations. To our knowledge, this is the largest scale semantic tagging effort...

Exploiting Syntactic and Semantic Information for Relation Extraction from Wikipedia

DPT Nguyen — 2008-01-18T15:53:52-00:00

IJCAI Workshop on Text-Mining \& Link-Analysis (TextLink 2007) (2007)

A cooccurrence-based thesaurus and two applications to information retrieval

H Schütze — 2008-01-18T15:46:56-00:00

Information Processing and Management, Vol. 33, No. 3. (1997), pp. 307-318.

Automatic Thesaurus Generation for an Electronic Community System

Chen — 2008-01-18T15:45:03-00:00

Journal of the American Society for Information Science (1995)

This research reports an algorithmic approach to the automatic generation of thesauri for electronic community systems. The techniques used included term filtering, automatic indexing, and cluster analysis. The testbed for our research was the Worm Community System, which contains a comprehensive library of specialized community data and literature, currently in use by molecular biologists who study the nematode worm C. elegans. The resulting worm thesaurus included 2709 researchers’ names, 798 gene names, 20 experimental methods, and 4302 subject descriptors. On average, each term had about 90 weighted neighboring terms indicating relevant concepts. The thesaurus was developed as an online search aide. We tested the worm thesaurus in an experiment with six worm researchers of varying degrees of expertise and background. The experiment showed that the thesaurus was an excellent “memory-jogging” device and that it supported learning and serendipitous browsing. Despite some occurrences of obvious noise, the system was useful in suggesting relevant concepts for the researchers’ queries and it helped improve concept recall. With a simple browsing interface, an automatic thesaurus can become a useful tool for online search and can assist researchers in exploring and traversing a dynamic and complex electronic community system.

Lexical Acquisition: Exploiting On-Line Resources to Build a Lexicon

U Zernik — 2008-01-18T15:35:50-00:00

(1991)

The PageRank Citation Ranking: Bringing Order to the Web

Lawrence Page — 2004-12-10T12:22:03-00:00

(1998)

The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a method for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them. We compare PageRank to an idealized random Web surfer. We show how to efficiently compute PageRank for large...

PageRank, HITS and a Unified Framework for Link Analysis

Chris Ding — 2005-10-03T10:38:25-00:00

No. 49372. (2002)

Two popular webpage ranking algorithms are HITS and PageRank. HITS emphasizes mutual reinforcement between authority and hub webpages, while PageRank emphasizes hyperlink weight normalization and web surfing based on random walk models. We systematically generalize /combine these concepts into a unified framework. The ranking framework contains a large algorithm space

The Impact of Semantic Handshakes

Lutz Maicher — 2008-01-18T14:52:11-00:00

Leveraging the Semantics of Topic Maps (2007), pp. 140-151.

One of the key challenges for the breaking through of the semantic web or web 2.0 is global semantic integration: if two proxies in different subject-centric models represent the same subject in the “real world” they should become mergeable. The common top-down approach to semantic integration is the enforcement of centralised ontologies, vocabularies or PSI repositories. This top-down approach bases on an overly optimistic premise: the success of one universal vocabulary enforced by a central authority. This paper proposes a bottom-up approach. A semantic handshake is the decision that two terms from different vocabularies can be used to identify the same subject. If these local decisions are broadcasted, global integration can be achieved without any ontological imperialism. Within this paper this hypothesis is investigated by simulations. We show that if the majority of proxies describes its identity only by two different public known terms, global integration is almost achievable at the large scale.

Handbook on Ontologies (International Handbooks on Information Systems)

Steffen Staab — 2005-03-07T11:58:21-00:00

(22 January 2004)

An ontology is a description (like a formal specification of a program) of concepts and relationships that can exist for an agent or a community of agents. The concept is important for the purpose of enabling knowledge sharing and reuse. The Handbook on Ontologies provides a comprehensive overview of the current status and future prospectives of the field of ontologies. The handbook demonstrates standards that have been created recently, it surveys methods that have been developed and it shows how to bring both into practice of ontology infrastructures and applications that are the best of their kind.

Semantic taxonomy induction from heterogenous evidence

Rion Snow — 2007-05-24T12:51:17-00:00

(2006), pp. 801-808.

Semantic integration: a survey of ontology-based approaches

Natalya Noy — 2005-01-31T15:52:37-00:00

SIGMOD Rec., Vol. 33, No. 4. (December 2004), pp. 65-70.

Usability and the Semantic Web

Anthony Jameson — 2007-05-18T09:41:07-00:00

The Semantic Web: Research and Applications (2006), pp. 3-3.

In addition to its technical implications, the semantic web vision gives rise to some challenges concerning usability and interface design. What difficulties can arise when persons with little or no relevant training try to (a) formulate knowledge (e.g., with ontology editors or annotation tools) in such a way that it can be exploited by semantic web technologies; or (b) leverage semantic information while querying or browsing? What strategies have been applied in an effort to overcome these difficulties, and what are the main open issues that remain? This talk will address these questions, referring to examples and results from a variety of research efforts, including the project SemIPort, which concerns semantic methods and tools for information portals, and Halo 2, in which tools have been developed and evaluated that enable scientists to formalize and query college-level scientific knowledge.

Towards a standard upper ontology

I Niles — 2006-12-15T10:18:36-00:00

(2001)

The Suggested Upper Merged Ontology (SUMO) is an upper level ontology that has been proposed as a starter document for The Standard Upper Ontology Working Group, an IEEE-sanctioned working group of collaborators from the fields of engineering, philosophy, and information science. The SUMO provides definitions for general-purpose terms and acts as a foundation for more specific domain ontologies. In this paper we outline the strategy used to create the current version of the SUMO, discuss some...

Cyc: toward programs with common sense

Douglas Lenat — 2005-10-18T07:57:52-00:00

Commun. ACM, Vol. 33, No. 8. (August 1990), pp. 30-49.

WordNet: An Electronic Lexical Database (Language, Speech, and Communication)

Fellbaum — 2005-03-04T15:24:02-00:00

(15 May 1998)

with a preface by George Miller WordNet, an electronic lexical database, is considered to be the most important resource available to researchers in computational linguistics, text analysis, and many related areas. Its design is inspired by current psycholinguistic and computational theories of human lexical memory. English nouns, verbs, adjectives, and adverbs are organized into synonym sets, each representing one underlying lexicalized concept. Different relations link the synonym sets. The purpose of this volume is twofold. First, it discusses the design of WordNet and the theoretical motivations behind it. Second, it provides a survey of representative applications, including word sense identification, information retrieval, selectional preferences of verbs, and lexical chains. Contributors: Reem Al-Halimi, Robert C. Berwick, J. F. M. Burg, Martin Chodorow, Christiane Fellbaum, Joachim Grabowski, Sanda Harabagiu, Marti A. Hearst, Graeme Hirst, Douglas A. Jones, Rick Kazman, Karen T. Kohl, Shari Landes, Claudia Leacock, George A. Miller, Katherine J. Miller, Dan Moldovan, Naoyuki Nomura, Uta Priss, Philip Resnik, David St-Onge, Randee Tengi, Reind P. van de Riet, Ellen Voorhees.

Combining Linguistic and Statistical Analysis to Extract Relations from Web Documents

FM Suchanek — 2008-01-18T14:40:22-00:00

Exploiting Wikipedia as External Knowledge for Named Entity Recognition

Jun'ichi Kazama — 2008-01-18T14:25:13-00:00

(2007), pp. 698-707.

We explore the use of Wikipedia as external knowledge to improve named entity recognition (NER). Our method retrieves the corresponding Wikipedia entry for each candidate word sequence and extracts a category label from the first sentence of the entry, which can be thought of as a definition part. These category labels are used as features in a CRF-based NE tagger. We demonstrate using the CoNLL 2003 dataset that the Wikipedia category labels extracted by such a simple method actually improve the accuracy of NER.

Use of Wikipedia Categories in Entity Ranking

JA Thom — 2008-01-18T14:20:07-00:00

Proceedings of the 12th Australasian Document Computing Symposium, Melbourne, Australia (2007)

Analyzing and Accessing Wikipedia as a Lexical Semantic Resource

T Zesch — 2008-01-18T14:20:07-00:00

Biannual Conference of the Society for Computational Linguistics and Language Technology (2007), pp. 213-221.

Large-Scale Named Entity Disambiguation Based on Wikipedia Data

S Cucerzan — 2008-01-18T14:20:07-00:00

EMNLP 2007: Empirical Methods in Natural Language Processing, June 28-30, 2007, Prague, Czech Republic (2007)

Using Encyclopedic Knowledge for Named Entity Disambiguation

R Bunescu — 2008-01-18T14:20:07-00:00

Proceedings of the 11th Conference of the European Chapter of the Association for Computational Linguistics (EACL-06) (2006)