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Title:Probabilistic Score Propagation in Information Retrieval
Author(s):Shakery, Azadeh
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):Computer Science
Abstract:We study three applications of this framework for improving retrieval accuracy in three different areas: "Hypertext Retrieval", "Smoothing of Document Language Models" and "Cross-Language Information Retrieval". The experiment results show that the score propagation framework provides a general effective way of exploiting link information along with the content information to improve the retrieval accuracy.
Issue Date:2008
Type:Text
Language:English
Description:119 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2008.
URI:http://hdl.handle.net/2142/81816
Other Identifier(s):(MiAaPQ)AAI3314889
Date Available in IDEALS:2015-09-25
Date Deposited:2008


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