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Proceedings of the seventh international conference on Information and knowledge management
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SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
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SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
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SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
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Proceedings of the 8th ACM international workshop on Data warehousing and OLAP
Proceedings of the 8th ACM international workshop on Data warehousing and OLAP
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Proceedings of the 2007 ACM SIGMOD international conference on Management of data
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Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
ADBIS'10 Proceedings of the 14th east European conference on Advances in databases and information systems
A quad-tree based multiresolution approach for two-dimensional summary data
Information Systems
Proceedings of the ACM 14th international workshop on Data Warehousing and OLAP
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Proceedings of the ACM 14th international workshop on Data Warehousing and OLAP
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
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BNCOD'05 Proceedings of the 22nd British National conference on Databases: enterprise, Skills and Innovation
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BNCOD'06 Proceedings of the 23rd British National Conference on Databases, conference on Flexible and Efficient Information Handling
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This paper extends a quad-tree based multi-resolution approach for two-dimensional summary data by providing a novel OLAP data cube compression approach that keeps the critical novelty of relying on R-tree based partitions instead of more constrained classical kinds of partition. This important novelty introduces the nice amenity of (i) allowing end-users to exploit the semantics of data and (ii) obtaining compressed representations of data cubes where more space can be invested to describe those ranges of multidimensional data for which they retain a higher degree of interest. Hence, this paper can be considered as an important advancement over the state-of-the-art approaches. Experimental results confirm the benefits of our proposed approach.