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Title:Improve KL -Divergence Language Models in Information Retrieval Using Corpus Local Structures
Author(s):Tao, Tao
Doctoral Committee Chair(s):Zhai, ChengXiang
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Information Science
Abstract:In summary, this thesis studies KL-divergence from different perspectives and proposes several new models to address the existing problems in KL-divergence language models. It results in more effective retrieval models, which should potentially benefit all retrieval applications.
Issue Date:2007
Type:Text
Language:English
Description:95 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.
URI:http://hdl.handle.net/2142/81805
Other Identifier(s):(MiAaPQ)AAI3301233
Date Available in IDEALS:2015-09-25
Date Deposited:2007


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