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Title:Enabling Data Retrieval: By Ranking and Beyond
Author(s):Li, Chengkai
Doctoral Committee Chair(s):Chang, Kevin Chen-Chuan
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:This thesis further studies how to enable retrieval mechanisms beyond just ranking. Our explorative study in this direction is exemplified by two novel proposals---One is to integrate clustering and ranking of database query results; the other is to support inverse ranking queries that provide ranks of objects in query context. Injecting such non-traditional facilities into databases presents non-trivial challenges in both defining query semantics and designing query processing methods. We extended SQL language to express such queries and invented partition- and summary-driven approaches to process them.
Issue Date:2007
Type:Text
Language:English
Description:176 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2007.
URI:http://hdl.handle.net/2142/81783
Other Identifier(s):(MiAaPQ)AAI3290293
Date Available in IDEALS:2015-09-25
Date Deposited:2007


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