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Enabling OLAP in mobile environments via intelligent data cube compression techniques
The main drawbacks of handheld devices (small storage space, small size of the display screen, discontinuance of the connection to the WLAN etc) are often incompatible with the need of querying and browsing information extracted from enormous amounts of data which are accessible through the network....
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Published in: | Journal of intelligent information systems 2009-10, Vol.33 (2), p.95-143 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The main drawbacks of handheld devices (small storage space, small size of the display screen, discontinuance of the connection to the WLAN etc) are often incompatible with the need of querying and browsing information extracted from enormous amounts of data which are accessible through the network. In this application scenario, data compression and summarization have a leading role: data in a lossy compressed format can be transmitted more efficiently than the original ones, and can be effectively stored in handheld devices (setting the compression ratio accordingly). In this paper, we introduce a very effective compression technique for multidimensional data cubes, and the system Hand-OLAP, which exploits this technique to allow handheld devices to extract and browse compressed two-dimensional OLAP views coming from multidimensional data cubes stored on a remote OLAP server localized on the wired network. Hand-OLAP effectively and efficiently enables OLAP in mobile environments, and also enlarges the potentialities of Decision Support Systems by taking advantage from the “naturally” decentralized nature of such environments. The idea which the system is based on is: rather than querying the original multidimensional data cubes, it may be more convenient to generate a compressed OLAP view of them, store such view into the handheld device, and query it locally (off-line), thus obtaining approximate answers that are suitable for OLAP applications. |
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ISSN: | 0925-9902 1573-7675 |
DOI: | 10.1007/s10844-008-0065-4 |