Detecting document genre for personalization of information retrieval

Gheorghe Muresan, Catherine L. Smith, Michael Cole, Lu Liu, Nicholas J. Belkin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

We report on the effectiveness of language models for personalization of retrieval results based on a searcher's preference for document genre. In principle, such preferences can be obtained via implicit relevance feedback through the observation of the searcher's actions and behavior during search sessions. While our approach did not produce significant improvement to retrieval effectiveness, the methodology and experimental setting can and are being used for further work on exploring genre-based personalization.

Original languageEnglish (US)
Title of host publicationProceedings of the 39th Annual Hawaii International Conference on System Sciences, HICSS'06
Pages50c
DOIs
StatePublished - 2006
Event39th Annual Hawaii International Conference on System Sciences, HICSS'06 - Kauai, HI, United States
Duration: Jan 4 2006Jan 7 2006

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume3
ISSN (Print)1530-1605

Other

Other39th Annual Hawaii International Conference on System Sciences, HICSS'06
Country/TerritoryUnited States
CityKauai, HI
Period1/4/061/7/06

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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