Depth-k skyline query for unquantifiable attributes in distributed systems

Yi Chung Chen, Chiang Lee

研究成果: Conference contribution

5 引文 斯高帕斯(Scopus)

摘要

Skyline query has been a research issue attracting much attention in recent years. However, the need of dealing with attributes of unquantifiable values in such a query has not been noticed so far. These attributes of unquantifiable values (or unquantifiable attribute in short) usually contain important information that is unignorable in query processing. In this paper, we propose the notion of depth-k skyline query to address this issue. We specifically study this issue in a distributed system environment as it is the most common environment we are facing today. We propose two sifters to accelerate the query processing. The neural network technology is employed in the sifter, which significantly reduces the cost of the query processing. Extensive simulations demonstrate both the effectiveness and the efficiency of the proposed technique.

原文English
主出版物標題Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing, ASC 2011
頁面315-322
頁數8
DOIs
出版狀態Published - 2011 十二月 1
事件14th IASTED International Conference on Artificial Intelligence and Soft Computing, ASC 2011 - Crete, Greece
持續時間: 2011 六月 222011 六月 24

出版系列

名字Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing, ASC 2011

Other

Other14th IASTED International Conference on Artificial Intelligence and Soft Computing, ASC 2011
國家/地區Greece
城市Crete
期間11-06-2211-06-24

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 軟體

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