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NSF Report (24 June 2008)
by Christine, Hal Abelson, Lee Dirks, et al.Roberta Johnson, Kenneth R. Koedinger, Marcia C. Linn, Clifford A. Lynch, Diana G. Oblinger, Roy D. Pea, Katie Salen, Marshall S. Smith, Alex Szalay
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innovate, Vol. 2, No. 5. (June 2006)
posted to no-tag
by seungwon
to the group VT_DLRL
on 2008-09-10 20:33:42
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Abstract
The Memex Metadata for Student Portfolios (M2) project is using mobile technology to augment student memory and improve student learning. We have constructed a student-targeted Context Awareness Framework (CAF) and we are developing a metadata scheme that integrates the CAF with a variety of mobile technologies. In particular, we are exploring the use of Microsoft SenseCams, which capture images and sensory data approximately every 90 seconds and can extend student memory, enabling for an enriched learning experience for undergraduate biology students. ...
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Educause Center for Applied Research, Vol. 2008, No. 18. (2 September 2008)
posted to no-tag
by seungwon
to the group VT_DLRL
on 2008-09-04 20:13:46
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(2002)
posted to digital_library
by seungwon
to the group VT_DLRL
on 2008-08-21 22:18:48
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Data Mining and Knowledge Discovery, Vol. 1, No. 3. (1997), pp. 259-289
posted to episode frequent
by seungwon
to the group VT_DLRL
on 2007-11-25 19:35:13
Abstract
Sequences of events describing the behavior and actions of users or systems can be collected in several domains. We consider the problem of discovering frequently occurring episodes in such sequences. An episode is defined to be a collection of events that occur relatively close to each other in a given partial order. Once such episodes are known, one can produce rules for describing or predicting the behavior of the sequence. We give efficient algorithms for the discovery of all frequent... ...
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posted to creativity vr
by seungwon
to the group VT_DLRL
on 2007-10-10 03:19:10
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posted to no-tag
by seungwon
to the group VT_DLRL
on 2007-10-10 03:17:54
along with 2 people
erisu
klshivel
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posted to secondlife
by seungwon
to the group VT_DLRL
on 2007-10-10 03:14:51
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In ITiCSE '07: Proceedings of the 12th annual SIGCSE conference on Innovation and technology in computer science education (2007), pp. 329-329, doi:10.1145/1268784.1268897
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Abstract
Video games can teach science and engineering better than lectures. Are they a cure for a numbing 200-person class? ...
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The Computer Journal, Vol. 42, No. 2. (???? 1999), pp. 100-111
posted to no-tag
by seungwon
to the group VT_DLRL
on 2007-09-12 16:47:04
Abstract
this paper, we also consider the approximate dependency inference task: given a relation r and a threshold #, find all minimal non-trivial approximate dependencies ...
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In Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining (2005), pp. 364-373, doi:10.1145/1081870.1081912
Abstract
Redescription mining is a newly introduced data mining problem that seeks to find subsets of data that afford multiple definitions. It can be viewed as a generalization of association rule mining, from finding implications to equivalences; as a form of conceptual clustering, where the goal is to identify clusters that afford dual characterizations; and as a form of constructive induction, to build features based on given descriptors that mutually reinforce each other. In this paper, we present the use of redescription ...
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Abstract
Previous research has shown that researchers can generate medical hypotheses by using computers to analyze several, seemingly unrelated, medical literatures. In this work we suggest broader application for the ideas of literature-based discovery. Specifically, we suggest that literature-based discovery can be fruitful in areas other than medicine; that in addition to finding "cures" for "problems," literature-based discovery offers the possibility of finding new problems for existing technologies; that the analysis of a single literature may be sufficient for literature-based discovery; and ...
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(1983)
Abstract
An abstract is not available. ...
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Abstract
An abstract is not available. ...
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Pattern Recognition, Vol. 30, No. 7. (1997), pp. 1145-1159
posted to classification
by xiaoyan2006
to the group VT_DLRL
on 2007-07-31 18:51:21
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Machine Learning, Vol. 42, No. 3. (2001), pp. 203-231
Abstract
In real-world environments it usually is difficult to specify target operating conditions precisely, for example, target misclassification costs. This uncertainty makes building robust classification systems problematic. We show that it is possible to build a hybrid classifier that will perform at least as well as the best available classifier for any target conditions. In some cases, the performance of the hybrid actually can surpass that of the best known classifier. This robust performance... ...
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Abstract
Receiver operating characteristics (ROC) graphs are useful for organizing classifiers and visualizing their performance. ROC graphs are commonly used in medical decision making, and in recent years have been used increasingly in machine learning and data mining research. Although ROC graphs are apparently simple, there are some common misconceptions and pitfalls when using them in practice. The purpose of this article is to serve as an introduction to ROC graphs and as a guide for using them in research. ...
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(2004)
Abstract
The area under an ROC curve (AUC) is a criterion used in many applications to measure the quality of a classification algorithm. However, the objective function optimized in most of these algorithms is the error rate and not the AUC value. We give a detailed statistical analysis of the relationship between the AUC and the error rate, including the first exact expression of the expected value and the variance of the AUC for a fixed error rate. Our results show that the average AUC is... ...
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(2003)
posted to classification
by xiaoyan2006
to the group VT_DLRL
on 2007-07-10 21:22:05
Abstract
Cross entropy and mean squared error are typical cost functions used to optimize classifier performance. The goal of the optimization is usually to achieve the best correct classification rate. However, for many two-class real-world problems, the ROC curve is a more meaningful performance measure. We demonstrate that minimizing cross entropy or mean squared error does not necessarily maximize the area under the ROC curve(AUC). We then consider alternative objective functions for training a... ...
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Library Trends, Special Issue on Assessing and Evaluating Digital Library Services, Vol. 49, No. 2. (2000), pp. 228-250
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(1986)
Abstract
An abstract is not available. ...
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In Proceedings of the 38th Technical Symposium on Computer Science Education (SIGCSE 2007), Vol. 39, No. 1. (March 2007), pp. 55-59
posted to syllabus
by xiaoyan2006
to the group VT_DLRL
on 2007-06-22 14:42:35
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In Proceedings of the 4th International Workshop on Applications of Semantic Web Technologies for E-Learning (SW-EL) (2006)
posted to ie
by xiaoyan2006
to the group VT_DLRL
on 2007-06-22 14:37:46
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In The 10th International Conference on Asian Digital Libraries (ICADL) (2007)
posted to ie
by xiaoyan2006
to the group VT_DLRL
on 2007-06-22 14:31:51
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In Encyclopedia of Data Warehousing and Mining (2008)
posted to classification
by xiaoyan2006
to the group VT_DLRL
on 2007-06-22 14:24:23
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(1999)
Abstract
Smoothing methods, extensively used for solving important mathematical programming problems and applications, are applied here to generate and solve an unconstrained smooth reformulation of the support vector machine for pattern classification using a completely arbitrary kernel. We term such reformulation a smooth support vec- tor machine (SSVM). A fast Newton-Armijo algorithm for solving the SSVM converges globally and quadratically. Numerical results and comparisons are given to... ...
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J. Mach. Learn. Res. In SIGIR '91: Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval, Vol. 5 (December 2004), pp. 361-397, doi:10.1145/122860.122861
Abstract
Reuters Corpus Volume I (RCV1) is an archive of over 800,000 manually categorized newswire stories recently made available by Reuters, Ltd. for research purposes. Use of this data for research on text categorization requires a detailed understanding of the real world constraints under which the data was produced. Drawing on interviews with Reuters personnel and access to Reuters documentation, we describe the coding policy and quality control procedures used in producing the RCV1 data, the intended semantics of the hierarchical category ...
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In Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval (1999), pp. 42-49, doi:10.1145/312624.312647
Abstract
An abstract is not available. ...
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Abstract
Exploring services for digital libraries (DLs) include two major paradigms, browsing and searching, as well as other services such as clustering and visualization. In this paper, we formalize and generalize DL exploring services within a DL theory. We develop theorems to indicate that browsing and searching can be converted or mapped to each other under certain conditions. The theorems guide the design and implementation of exploring services for an integrated archaeological DL, ETANA-DL. Its integrated browsing and searching can support users ...
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Abstract
This paper explores the use of social annotations to improve websearch. Nowadays, many services, e.g. del.icio.us, have been developed for web users to organize and share their favorite webpages on line by using social annotations. We observe that the social annotations can benefit web search in two aspects: 1) the annotations are usually good summaries of corresponding webpages; 2) the count of annotations indicates the popularity of webpages. Two novel algorithms are proposed to incorporate the above information into page ranking: ...
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(1998)
Abstract
Recent approaches to text classification have used two di#erent first-order probabilistic models for classification, both of which make the naive Bayes assumption. ...
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(1995), pp. 338-345
Abstract
When modeling a probability distribution with a Bayesian network, we are faced with the problem of how to handle continuous variables. Most previous work has either solved the problem by discretizing, or assumed that the data are generated by a single Gaussian. In this paper we abandon the normality assumption and instead use statistical methods for nonparametric density estimation. For a naive Bayesian classifier, we present experimental results on a variety of natural and artificial domains,... ...
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In VI Brazilian Symposium on GeoInformatics (2004)
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No. IC-0303. (January 2003)
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