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Conference Paper: Capturing user reading behaviors for personalized document summarization
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TitleCapturing user reading behaviors for personalized document summarization
 
AuthorsJiang, H1
Xu, S2
Lau, FCM1
 
KeywordsPersonalized document summarization
Reading preference
Personal preferences
Facial expressions
Gaze positions
Reading durations
 
Issue Date2011
 
PublisherAssociation for Computing Machinery.
 
CitationThe 16th international conference on Intelligent user interfaces (IUI'11), Palo Alto, CA., 13-16 February 2011. In Proceedings of 16th IUI, 2011, p. 355-358 [How to Cite?]
DOI: http://dx.doi.org/10.1145/1943403.1943464
 
AbstractWe propose a new personalized document summarization method, which observes a user's reading behaviors, including user facial expressions, gaze positions, and reading durations, during his or her past reading activities to infer the user's personal reading preferences. Once a user's personal reading preferences are derived, our algorithm can then automatically generate document summarization in a personalized way. We compare the performance of our algorithm with that of a few peer algorithms and software packages. The result of our comparative study shows that our algorithm can produce superior personalized document summaries than those peer methods in that the automatic document summarization generated by our algorithm can better satisfy a user's personal preferences. © 2011 ACM.
 
ISBN978-1-4503-0419-1
 
DOIhttp://dx.doi.org/10.1145/1943403.1943464
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorJiang, H
 
dc.contributor.authorXu, S
 
dc.contributor.authorLau, FCM
 
dc.date.accessioned2012-06-26T06:32:16Z
 
dc.date.available2012-06-26T06:32:16Z
 
dc.date.issued2011
 
dc.description.abstractWe propose a new personalized document summarization method, which observes a user's reading behaviors, including user facial expressions, gaze positions, and reading durations, during his or her past reading activities to infer the user's personal reading preferences. Once a user's personal reading preferences are derived, our algorithm can then automatically generate document summarization in a personalized way. We compare the performance of our algorithm with that of a few peer algorithms and software packages. The result of our comparative study shows that our algorithm can produce superior personalized document summaries than those peer methods in that the automatic document summarization generated by our algorithm can better satisfy a user's personal preferences. © 2011 ACM.
 
dc.description.naturelink_to_OA_fulltext
 
dc.description.otherThe 16th international conference on Intelligent user interfaces (IUI'11), Palo Alto, CA., 13-16 February 2011. In Proceedings of 16th IUI, 2011, p. 355-358
 
dc.identifier.citationThe 16th international conference on Intelligent user interfaces (IUI'11), Palo Alto, CA., 13-16 February 2011. In Proceedings of 16th IUI, 2011, p. 355-358 [How to Cite?]
DOI: http://dx.doi.org/10.1145/1943403.1943464
 
dc.identifier.doihttp://dx.doi.org/10.1145/1943403.1943464
 
dc.identifier.epage358
 
dc.identifier.hkuros211555
 
dc.identifier.isbn978-1-4503-0419-1
 
dc.identifier.scopuseid_2-s2.0-79952774990
 
dc.identifier.spage355
 
dc.identifier.urihttp://hdl.handle.net/10722/151998
 
dc.languageeng
 
dc.publisherAssociation for Computing Machinery.
 
dc.publisher.placeUnited States
 
dc.relation.ispartofProceedings of the International Conference on Intelligent User Interfaces, IUI 2011
 
dc.relation.referencesReferences in Scopus
 
dc.rightsProceedings of the 16th international conference on Intelligent user interfaces, IUI'11. Copyright © Association for Computing Machinery.
 
dc.rights©ACM, 2011. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the 16th International Conference on Intelligent User Interfaces, 2011, http://doi.acm.org/10.1145/1943403.1943464
 
dc.subjectPersonalized document summarization
 
dc.subjectReading preference
 
dc.subjectPersonal preferences
 
dc.subjectFacial expressions
 
dc.subjectGaze positions
 
dc.subjectReading durations
 
dc.titleCapturing user reading behaviors for personalized document summarization
 
dc.typeConference_Paper
 
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Author Affiliations
  1. The University of Hong Kong
  2. Oak Ridge National Laboratory