Scalable ranking for preference queries

Ying Feng, Divyakant Agrawal, Amr El Abbadi, Ambuj Singh

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

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.

Original languageEnglish
Title of host publicationInternational Conference on Information and Knowledge Management, Proceedings
Pages313-314
Number of pages2
DOIs
Publication statusPublished - 1 Dec 2005
Externally publishedYes
EventCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management - Bremen, Germany
Duration: 31 Oct 20055 Nov 2005

Other

OtherCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management
CountryGermany
CityBremen
Period31/10/055/11/05

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Keywords

  • Preference queries
  • Query Optimization

ASJC Scopus subject areas

  • Business, Management and Accounting(all)

Cite this

Feng, Y., Agrawal, D., El Abbadi, A., & Singh, A. (2005). Scalable ranking for preference queries. In International Conference on Information and Knowledge Management, Proceedings (pp. 313-314) https://doi.org/10.1145/1099554.1099643