Learning from past queries for resource selection

12 years 3 months ago
Learning from past queries for resource selection
Federated text search provides a unified search interface for multiple search engines of distributed text information sources. Resource selection is an important component for federated text search, which selects a small number of information sources that contain the largest number of relevant documents for a user query. Most prior research of resource selection focused on selecting information sources by analyzing static information of available information sources that is sampled in the offline manner. On the other hand, most prior research ignored a large amount of valuable information like the results from past queries. This paper proposes a new resource selection technique (which is called qSim) that utilizes the search results of past queries for estimating the utilities of available information sources for a specific user query. Experiment results demonstrate the effectiveness of the new resource selection algorithm. Categories and Subject Descriptors H.3.3 [Information Search ...
Suleyman Cetintas, Luo Si, Hao Yuan
Added 02 Sep 2010
Updated 02 Sep 2010
Type Conference
Year 2009
Where CIKM
Authors Suleyman Cetintas, Luo Si, Hao Yuan
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