Query expansion by mining user logs

Queries to search engines on the Web are usually short. They do not provide sufficient information for an effective selection of relevant documents. Previous research has proposed the utilization of query expansion to deal with this problem. However, expansion terms are usually determined on term co...

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Bibliographic Details
Published in:IEEE transactions on knowledge and data engineering 2003-07, Vol.15 (4), p.829-839
Main Authors: Cui, Hang, Wen, Ji-Rong, Nie, Jian-Yun, Ma, Wei-Ying
Format: Article
Language:English
Subjects:
Correlation
Correlation analysis
Indexing
Information retrieval
Judgments
Logs
Query processing
Search engines
Search methods
Statistical analysis
Thesauri
Utilization
Vocabulary
Web sites
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Summary:Queries to search engines on the Web are usually short. They do not provide sufficient information for an effective selection of relevant documents. Previous research has proposed the utilization of query expansion to deal with this problem. However, expansion terms are usually determined on term co-occurrences within documents. In this study, we propose a new method for query expansion based on user interactions recorded in user logs. The central idea is to extract correlations between query terms and document terms by analyzing user logs. These correlations are then used to select high-quality expansion terms for new queries. Compared to previous query expansion methods, ours takes advantage of the user judgments implied in user logs. The experimental results show that the log-based query expansion method can produce much better results than both the classical search method and the other query expansion methods.
ISSN:1041-4347
1558-2191
DOI:10.1109/TKDE.2003.1209002