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ABSTRACT: The widespread use of location-aware devices has led to countless
location-based services in which a user query can be arbitrarily complex, i.e.,
one that embeds multiple spatial selection and join predicates. Amongst these
predicates, the k-Nearest-Neighbor (kNN) predicate stands as one of the most
important and widely used predicates. Unlike related research, this paper goes
beyond the optimization of queries with single kNN predicates, and shows how
queries with two kNN predicates can be optimized. In particular, the paper
addresses the optimization of queries with: (i) two kNN-select predicates, (ii)
two kNN-join predicates, and (iii) one kNN-join predicate and one kNN-select
predicate. For each type of queries, conceptually correct query evaluation
plans (QEPs) and new algorithms that optimize the query execution time are
presented. Experimental results demonstrate that the proposed algorithms
outperform the conceptually correct QEPs by orders of magnitude.
07/2012;
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Distributed and Parallel Databases. 01/2011; 29:217-238.
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Workshops Proceedings of the 26th International Conference on Data Engineering, ICDE 2010, March 1-6, 2010, Long Beach, California, USA; 01/2010
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ACM Trans. Database Syst. 01/2009; 34.
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Proceedings of the 2nd SIGSPATIAL ACM GIS 2009 International Workshop on Security and Privacy in GIS and LBS, SPRINGL 2009, November 3, 2009, Seattle, WA, USA; 01/2009
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Proceedings of the 24th International Conference on Data Engineering, ICDE 2008, April 7-12, 2008, Cancún, México; 01/2008
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EDBT 2008, 11th International Conference on Extending Database Technology, Nantes, France, March 25-29, 2008, Proceedings; 01/2008
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ABSTRACT: Biologists are increasingly using databases for storing and managing their data. Biological databases typically consist of a mixture of raw data, metadata, sequences, annotations, and related data obtained from various sources. Current database technology lacks several functionalities that are needed by biological databases. In this paper, we introduce bdbms, an extensible prototype database management system for supporting biological data. bdbms extends the functionalities of current DBMSs to include: (1) Annotation and provenance management including storage, indexing, manipulation, and querying of annotation and provenance as first class objects in bdbms, (2) Local dependency tracking to track the dependencies and derivations among data items, (3) Update authorization to support data curation via content-based authorization, in contrast to identity-based authorization, and (4) New access methods and their supporting operators that support pattern matching on various types of compressed biological data types. This paper presents the design of bdbms along with the techniques proposed to support these functionalities including an extension to SQL. We also outline some open issues in building bdbms.
01/2007;
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8th International Conference on Mobile Data Management (MDM 2007), Mannheim, Germany, May 7-11, 2007; 01/2007
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8th International Conference on Mobile Data Management (MDM 2007), Mannheim, Germany, May 7-11, 2007; 01/2007
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19th International Conference on Scientific and Statistical Database Management, SSDBM 2007, 9-11 July 2007, Banff, Canada, Proceedings; 01/2007
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8th International Conference on Mobile Data Management (MDM 2007), Mannheim, Germany, May 7-11, 2007; 01/2007
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IEEE Trans. Knowl. Data Eng. 01/2007; 19:57-72.
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Data Knowl. Eng. 01/2007; 60:511-529.
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Proceedings of the 23rd International Conference on Data Engineering, ICDE 2007, The Marmara Hotel, Istanbul, Turkey, April 15-20, 2007; 01/2007
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SIGMOD Record. 01/2006; 35:3-8.
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ACM Trans. Database Syst. 01/2006; 31:1257-1304.
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Proceedings of the 32nd International Conference on Very Large Data Bases, Seoul, Korea, September 12-15, 2006; 01/2006
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7th International Conference on Mobile Data Management (MDM 2006), Nara, Japan, May 9-13, 2006; 01/2006
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Proceedings of the 22nd International Conference on Data Engineering, ICDE 2006, 3-8 April 2006, Atlanta, GA, USA; 01/2006