RUcore: Rutgers University Community Repository
Personalizing information retrieval using interaction behaviors in search sessions in different types of tasks
Descriptive
TitleInfo
Title
Personalizing information retrieval using interaction behaviors in search sessions in different types of tasks
Name
(type = personal)
NamePart
(type = family)
Liu
NamePart
(type = given)
Chang
NamePart
(type = date)
1983-
DisplayForm
Chang Liu
Role
RoleTerm
(authority = RULIB)
author
Name
(type = personal)
NamePart
(type = family)
Belkin
NamePart
(type = given)
Nicholas J
DisplayForm
Nicholas J Belkin
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
chair
Name
(type = personal)
NamePart
(type = family)
Gwizdka
NamePart
(type = given)
Jacek
DisplayForm
Jacek Gwizdka
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Muresan
NamePart
(type = given)
Smaranda
DisplayForm
Smaranda Muresan
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
internal member
Name
(type = personal)
NamePart
(type = family)
Kelly
NamePart
(type = given)
Diane
DisplayForm
Diane Kelly
Affiliation
Advisory Committee
Role
RoleTerm
(authority = RULIB)
outside member
Name
(type = corporate)
NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
(type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm
(authority = RULIB)
school
TypeOfResource
Text
Genre
(authority = marcgt)
theses
OriginInfo
DateCreated
(qualifier = exact)
2012
DateOther
(qualifier = exact);
(type = degree)
2012-10
CopyrightDate
(qualifier = exact)
2012
Place
PlaceTerm
(type = code)
xx
Language
LanguageTerm
(authority = ISO639-2b);
(type = code)
eng
Abstract
(type = abstract)
When using information retrieval (IR) systems, users often pose short and ambiguous query terms. It is critical for IR systems to obtain more accurate representation of users’ information need, their document preferences, and the context they are working in, and then incorporate them into the design of the systems to tailor retrieval to individual users. The proposed study is to personalize IR systems by tailoring search result content to individual users through the inference of useful documents during their information seeking episode, in different types of tasks. Specifically, this dissertation has two research goals: (1) generate predictive models of document usefulness based on multiple user behaviors as in different types of tasks; (2) generate predictive models of task type through observing users’ search behaviors. To address these research goals, this study analyzed data collected in a controlled lab experiment. Thirty-two students were invited to participate in the study, each worked on four search tasks, and these tasks were designed to be different types. During search sessions, all users’ interactions were recorded by multiple loggers. Predictive models of document usefulness and task type were generated using various statistical analysis methods. Our results demonstrate that multiple behavioral measures on both content pages and search result pages can be indicators of document usefulness. More importantly, task type affected the relationship between the behavioral measures and document usefulness, and it may therefore be necessary to build task-specific predictive models of document usefulness, which can achieve better prediction accuracy than a non-task specific predictive model. In addition, behavioral measures on within-session level and whole-session levels could be able to generate predictive models of task type. The results improve our understanding on how to infer users’ search context information and document usefulness from user behaviors, and then to use this knowledge to improve the information searcher’s experience; that is, to make their information search more effective and pleasurable. The research findings have theoretical and practical implications for using behavioral measures and taking account of contextual factors in the development of personalized IR systems. Future studies are suggested for making use of these findings as well as research on related issues.
Subject
(authority = RUETD)
Topic
Communication, Information and Library Studies
Subject
(authority = ETD-LCSH)
Topic
Information storage and retrieval systems
Subject
(authority = ETD-LCSH)
Topic
Computer users
RelatedItem
(type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
(type = RULIB)
ETD
Identifier
ETD_4310
PhysicalDescription
Form
(authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
xvii, 193 p. : ill.
Note
(type = degree)
Ph.D.
Note
(type = bibliography)
Includes bibliographical references
Note
(type = vita)
Includes vita
Note
(type = statement of responsibility)
by Chang Liu
Subject
(authority = ETD-LCSH)
Topic
Electronic information resource searching
Identifier
(type = hdl)
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000066894
RelatedItem
(type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
(type = local)
rucore19991600001
Location
PhysicalLocation
(authority = marcorg);
(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3GM8622
Genre
(authority = ExL-Esploro)
ETD doctoral
Back to the top
Rights
RightsDeclaration
(ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
Liu
GivenName
Chang
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
(encoding = w3cdtf);
(qualifier = exact);
(point = start)
2012-10-03 12:13:27
AssociatedEntity
Name
Chang Liu
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
Back to the top
Technical
FileSize
(UNIT = bytes)
3022848
OperatingSystem
(VERSION = 5.1)
windows xp
ContentModel
ETD
MimeType
(TYPE = file)
application/pdf
MimeType
(TYPE = container)
application/x-tar
FileSize
(UNIT = bytes)
3031040
Checksum
(METHOD = SHA1)
3e41703a1abf477f3a5e44de1664bc98cc27bcce
Back to the top
Statistical Profile