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Information / Relevance feedback / Relevance / Precision and recall / Document clustering / Cluster analysis / Query expansion / Ranking / Human–computer information retrieval / Information science / Information retrieval / Science


INTERACTIVE INFORMATION ORGANIZATION: TECHNIQUES AND EVALUATION A Dissertation Presented by ANTON LEUSKI
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Document Date: 2010-04-15 22:00:00


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File Size: 3,35 MB

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Company

Interactive Systems / /

Event

Person Communication and Meetings / /

Facility

UNIVERSITY OF MASSACHUSETTS AMHERST Directed / Library of Congress / UNIVERSITY OF MASSACHUSETTS AT AMHERST Ph.D. / University of Massachusetts Amherst / /

IndustryTerm

search strategies / ranked list search strategy / reinforcement learning algorithm / information search / algorithmic search strategy / Web search engines / search strategy / web-based search engine / on-line search engines / “wizard” tool / relevance feedback search strategies / average algorithm / /

Organization

MOSCOW STATE UNIVERSITY / Congress / Graduate School / Defense Advanced Research Projects Agency / INFORMATION ORGANIZATION / National Science Foundation / Department of Computer Science / University of Massachusetts Amherst / Chair Department / UNIVERSITY OF MASSACHUSETTS AMHERST Directed / Department of Commerce / UNIVERSITY OF MASSACHUSETTS AT AMHERST / All Rights Reserved INTERACTIVE INFORMATION ORGANIZATION / INTERACTIVE INFORMATION ORGANIZATION / /

Person

James F. Kurose / Christopher Raphael / Jeremy Pickens / David Frey / Victor Lavrenko / Michael Kositsky / W. Bruce Croft / Dawn Lawrie / Andrew Barto / David Jensen / David D. Jensen / David Fisher / James Allan / Bruce Croft / ANTON LEUSKI / Russell Swan / Stephen Cronen-Townsend / /

Position

author / advisor / Professor / Chair / representative / /

ProvinceOrState

Massachusetts / /

Technology

3-D / average algorithm / 2.1 Clustering Algorithm / search engine / reinforcement learning algorithm / Ward algorithms / 5.2 Algorithms / /

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