Scalable ranking for preference queries

Authors:
Ying Feng;Divyakant Agrawal;Amr El Abbadi;Ambuj Singh
Affiliations:
University of California, Santa Barbara, CA;University of California, Santa Barbara, CA;University of California, Santa Barbara, CA;University of California, Santa Barbara, CA
Venue:
Proceedings of the 14th ACM international conference on Information and knowledge management
Year:
2005

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Abstract

Top-k preference queries with multiple attributes are critical for decision-making applications. Previous research has concentrated on improving the computational efficiency mainly by using novel index structures and search strategies. Since current applications need to scale to terabytes of data and thousands of users, performance of such systems is strongly impacted by the amount of available memory. This paper proposes a scalable approach for memory-bounded top-k query processing.