Personalized top-k skyline queries in high-dimensional space

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• 作者：Jongwuk Lee ; Gae-won You ; Seung-won Hwang
• 关键词：Skyline queries ; Personalization ; Ranking
• 刊名：Information Systems
• 出版年：2009
• 出版时间：March 2009
• 年：2009
• 卷：34
• 期：1
• 页码：45-61
• 全文大小：594 K

文摘

As data of an unprecedented scale are becoming accessible, it becomes more and more important to help each user identify the ideal results of a manageable size. As such a mechanism, skyline queries have recently attracted a lot of attention for its intuitive query formulation. This intuitiveness, however, has a side effect of retrieving too many results, especially for high-dimensional data. This paper is to support personalized skyline queries as identifying “truly interesting” objects based on user-specific preference and retrieval size k. In particular, we abstract personalized skyline ranking as a dynamic search over skyline subspaces guided by user-specific preference. We then develop a novel algorithm navigating on a compressed structure itself, to reduce the storage overhead. Furthermore, we also develop novel techniques to interleave cube construction with navigation for some scenarios without a priori structure. Finally, we extend the proposed techniques for user-specific preferences including equivalence preference. Our extensive evaluation results validate the effectiveness and efficiency of the proposed algorithms on both real-life and synthetic data.