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A supervised learning approach to search of definitions
Xu, J; Cao, YB; Li, H; Zhao, M; Huang, YL
Source PublicationJOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
2006-05-01
Volume21Issue:3Pages:439-449
SubtypeArticle
AbstractThis paper addresses the issue of search of definitions. Specifically, for a given term, we are to find out its definition candidates and rank the candidates according to their likelihood of being good definitions. This is in contrast to the traditional methods of either generating a single combined definition or outputting all retrieved definitions. Definition ranking is essential for tasks. A specification for judging the goodness of a definition is given. In the specification, a definition is categorized into one of the three levels: good definition, indifferent definition, or bad definition. Methods of performing definition ranking are also proposed in this paper, which formalize the problem as either classification or ordinal regression. We employ SVM (Support Vector Machines) as the classification model and Ranking SVM as the ordinal regression model respectively, and thus they rank definition candidates according to their likelihood of being good definitions. Features for constructing the SVM and Ranking SVM models are defined, which represent the characteristics of terms, definition candidate, and their relationship. Experimental results indicate that the use of SVM and Ranking SVM can significantly outperform the baseline methods such as heuristic rules, the conventional information retrieval-Okapi, or SVM regression. This is true when both the answers are paragraphs and they are sentences. Experimental results also show that SVM or Ranking SVM models trained in one domain can be adapted to another domain, indicating that generic models for definition ranking can be constructed.
KeywordDefinition Search Text Mining Web Mining Web Search
WOS HeadingsScience & Technology ; Technology
WOS KeywordWEB
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Hardware & Architecture ; Computer Science, Software Engineering
WOS IDWOS:000238079200019
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9218
Collection09年以前成果
Affiliation1.Nankai Univ, Coll Software, Tianjin 300071, Peoples R China
2.Microsoft Res Asia, Beijing 100080, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Xu, J,Cao, YB,Li, H,et al. A supervised learning approach to search of definitions[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2006,21(3):439-449.
APA Xu, J,Cao, YB,Li, H,Zhao, M,&Huang, YL.(2006).A supervised learning approach to search of definitions.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,21(3),439-449.
MLA Xu, J,et al."A supervised learning approach to search of definitions".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 21.3(2006):439-449.
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