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Adaptive visualization for focused p...

Ahn, Jae-wook.

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Adaptive visualization for focused personalized information retrieval.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Adaptive visualization for focused personalized information retrieval./
Author:	Ahn, Jae-wook.
Description:	162 p.
Notes:	Source: Dissertation Abstracts International, Volume: 72-05, Section: A, page: .
Contained By:	Dissertation Abstracts International72-05A.
Subject:	Information Technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3447303
ISBN:	9781124526683

Adaptive visualization for focused personalized information retrieval.
Ahn, Jae-wook.

Adaptive visualization for focused personalized information retrieval. - 162 p.

Source: Dissertation Abstracts International, Volume: 72-05, Section: A, page: .

Thesis (Ph.D.)--University of Pittsburgh, 2010.

The new trend on the Web has totally changed today's information access environment. The traditional information overload problem has evolved into the qualitative level beyond the quantitative growth. The mode of producing and consuming information is changing and we need a new paradigm for accessing information.

ISBN: 9781124526683Subjects--Topical Terms:

1030799
Information Technology.

Adaptive visualization for focused personalized information retrieval.
LDR:02989nam 2200337 4500 001 1400565
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020 $a 9781124526683
035 $a (UMI)AAI3447303
035 $a AAI3447303
040 $a UMI $c UMI
100 1 $a Ahn, Jae-wook. $3 1679630
245 1 0 $a Adaptive visualization for focused personalized information retrieval.
300 $a 162 p.
500 $a Source: Dissertation Abstracts International, Volume: 72-05, Section: A, page: .
500 $a Adviser: Peter Porusilovsky.
502 $a Thesis (Ph.D.)--University of Pittsburgh, 2010.
520 $a The new trend on the Web has totally changed today's information access environment. The traditional information overload problem has evolved into the qualitative level beyond the quantitative growth. The mode of producing and consuming information is changing and we need a new paradigm for accessing information.
520 $a Personalized search is one of the most promising answers to this problem. However, it still follows the old interaction model and representation method of classic information retrieval approaches. This limitation can harm the potential of personalized search, with which users are intended to interact with the system, learn and investigate the problem, and collaborate with the system to reach the final goal.
520 $a This dissertation proposes to incorporate interactive visualization into personalized search in order to overcome the limitation. By combining the personalized search and the interactive visualization, we expect our approach will be able to help users to better explore the information space and locate relevant information more efficiently.
520 $a We extended a well-known visualization framework called VIBE (Visual Information Browsing Environment) and implemented Adaptive VIBE, so that it can fit into the personalized searching environment. We tested the effectiveness of this adaptive visualization method and investigated its strengths and weaknesses by conducting a full-scale user study.
520 $a We also tried to enrich the user models with named-entities considering the possibility that the traditional keyword-based user models could harm the effectiveness of the system in the context of interactive information retrieval.
520 $a The results of the user study showed that the Adaptive VIBE could improve the precision of the personalized search system and could help the users to find out a more diverse set of information. The named-entity based user model integrated into Adaptive VIBE showed improvements of precision of user annotations while maintaining the level of diverse discovery of information.
590 $a School code: 0178.
650 4 $a Information Technology. $3 1030799
650 4 $a Information Science. $3 1017528
690 $a 0489
690 $a 0723
710 2 $a University of Pittsburgh. $3 958527
773 0 $t Dissertation Abstracts International $g 72-05A.
790 1 0 $a Porusilovsky, Peter, $e advisor
790 $a 0178
791 $a Ph.D.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3447303