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"Conceptual Partitioning: An Efficient Method for Continuous
Nearest Neighbor Monitoring"
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Speaker:
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Kyriakos MOURATIDIS
PhD Candidate
Computer Science Department
Hong Kong University of Science & Technology (HKUST)
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Date:
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17 January 2005 (Tuesday) |
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Time:
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3:00 pm to 5:00 pm |
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Venue:
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Meeting Room 4.4, Level 4
School of Information Systems
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Given a set of objects P and a query point q, a k nearest neighbor (k-NN) query retrieves the k objects in P that lie closest to q. Even though the problem is well-studied for static datasets, the traditional methods do not extend to highly dynamic environments where multiple continuous queries require real-time results, and both objects and queries receive frequent location updates. In this presentation we describe conceptual partitioning (CPM), a comprehensive technique for the efficient monitoring of continuous NN queries. CPM achieves low running time by handling location updates only from objects that fall in the vicinity of some query (and ignoring the rest). It can be used with multiple, static or moving queries, and it does not make any assumptions about the object moving patterns. This work was presented in SIGMOD 2005.
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Kyriakos MOURATIDIS received his B.Sc. degree in Computer Science in 2002 from the Aristotle University of Thessaloniki, Greece. Currently, he is a Ph.D. candidate in the Computer Science Department at the Hong Kong University of Science and Technology, working under the supervision of Dr. Dimitris Papadias. His research interests include spatiotemporal databases, location-based services, data stream processing, and mobile computing. |
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We look forward to welcome you at this Research Talk. |
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