Query Expansion by Mining User Logs

Query Expansion by Mining User Logs (2003)

by Hang Cui , Ji-Rong Wen , Jian-Yun Nie , Wei-Ying Ma

Venue:	IEEE TRANSACTION ON KNOWLEDGE AND DATA ENGINEERING
Citations:	35 - 4 self

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Datum	Value	Source
TITLE	Query Expansion by Mining User Logs	INFERENCE
AUTHOR NAME	Hang Cui	user correction
AUTHOR NAME	Ji-Rong Wen	user correction
AUTHOR NAME	Jian-Yun Nie	user correction
AUTHOR NAME	Wei-Ying Ma	user correction
ABSTRACT	Queries to search engines on the Web are usually short. They do not provide sufficient evidence 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	user correction
YEAR	2003	INFERENCE
VENUE	IEEE TRANSACTION ON KNOWLEDGE AND DATA ENGINEERING	user correction
VENUE TYPE	JOURNAL	INFERENCE
PAGES	829--839	INFERENCE
VOLUME	15	INFERENCE
NUMBER	4	user correction
CITATIONS	38 found	ParsCit 1.0