Term weighting for information retrieval based on term’s discrimination power

One of the most important research topics in Information Retrieval is term weighting for document ranking and retrieval, such as TFIDF, BM25, etc. We propose a term weighting method that utilizes past retrieval results consisting of the queries that contain a particular term, retrieval documents, an...

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Bibliographic Details
Published in:Multimedia tools and applications 2014-07, Vol.71 (2), p.769-781
Main Authors: Li, Qing, Lee, Seungwoo, Jung, Hanmin, Lee, Yeong Su, Cho, Jae-Hyun, Song, Sa-kwang
Format: Article
Language:English
Subjects:
Analysis
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Discrimination
Documents
Image processing systems
Information retrieval
Judgments
Multimedia
Multimedia Information Systems
Queries
Query expansion
Relevance feedback
Retrieval
Special Purpose and Application-Based Systems
Studies
Weighting
Weighting methods
Citations: Items that this one cites
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Summary:One of the most important research topics in Information Retrieval is term weighting for document ranking and retrieval, such as TFIDF, BM25, etc. We propose a term weighting method that utilizes past retrieval results consisting of the queries that contain a particular term, retrieval documents, and their relevance judgments. A term’s Discrimination Power(DP) is based on the difference degree of the term’s average weights obtained from between relevant and non-relevant retrieved document sets. The difference based DP performs better compared to ratio based DP introduced in the previous research. Our experimental result shows that a term weighting scheme based on the discrimination power method outperforms a TF*IDF based scheme.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-013-1420-1