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Personalized Search: An Interactive and Iterative Approach Open Access


Other title
personalized search
machine learning
relevance feedback
Type of item
Degree grantor
University of Alberta
Author or creator
Wang, Haiming
Supervisor and department
Wong, Kenny (Computing Science)
Examining committee member and department
Stroulia, Eleni (Computing Science)
Zaiane, Osmar R. (Computing Science)
Department of Computing Science

Date accepted
Graduation date
Master of Science
Degree level
In the face of an overwhelmingly information intensive Internet, searching has become the most important way to locate information efficiently. Current searching techniques are able to retrieve relevant data, however, personalization techniques are still needed to better identify different user requirements. This thesis proposes an interactive and iterative approach to infer a user's intentions implicitly, and adapt to changing user requirements. We gather relevance feedback from the user, and classify items in the query result set into different groups based on the feedback for each item. We rerank the original result set according to the user's interest towards each group. The group of the user's interest is ranked higher. We illustrate the approach using a personalized academic paper searching application and evaluate it with real users. The experimental results show improvements after applying our approach. The system design is extensible and potentially applicable to other search domains.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
Haiming Wang and Kenny Wong. Personalized search: an interactive and iterative approach. In Proceedings of the 2nd International Workshop on Personalized Web Tasking at the 10th World Congress on Services. IEEE, 2014.

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