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Personalized information retrieval in digital ecosystems

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Open access
Authors
Zhu, Dengya
Dreher, Heinz
Date
2008
Type
Conference Paper

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Citation
Zhu, Dengya and Dreher, Heinz. 2008. : Personalized information retrieval in digital ecosystems, in Chang, Elizabeth and Hussain, Farookh Khadeer (ed), Second IEEE international conference on digital ecosystems and technologies (IEEE DEST 2008), 26 Feb 2008, pp. 580-585. Phitsanulok, Thailand: IEEE.
Source Title
Second IEEE international conference on digital ecosystems and technologies (IEEE DEST 2008)
Source Conference
Second IEEE international conference on digital ecosystems and technologies (IEEE DEST 2008)
DOI
Faculty
Curtin Business School
School of Information Systems
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Copyright 2008 IEEE

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Abstract

Search results personalization is considered a promising approach to boost the quality of text retrieval. In this paper, a personalized information retrieval paradigm is proposed which not only implicitly creates user profile by learning users? search history, search preferences, and desktop information by kNN algorithm; but also intends to deal with the problem of search concepts drift through adjusting theweight of category which represents users? search preference.By comparing the cosine similarities between vectors represent personal valued search concepts in user profiles, and vectors represent search concepts in the retrieved search results, the search results will be tailed to better match users? information needs.