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Item Details
| Title:
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DATA MINING, ROUGH SETS AND GRANULAR COMPUTING
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| By: |
Tsau Young Lin (Editor), Yiyu Yao (Editor), Lotfi A. Zadeh (Editor) |
| Format: |
Paperback |
| List price:
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£171.00 |
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We currently do not stock this item, please contact the publisher directly for
further information.
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| ISBN 10: |
3790825085 |
| ISBN 13: |
9783790825084 |
| Publisher: |
SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG |
| Pub. date: |
21 October, 2010 |
| Edition: |
Softcover reprint of hardcover 1st ed. 2002 |
| Series: |
Studies in Fuzziness and Soft Computing 95 |
| Pages: |
537 |
| Synopsis: |
During the past few years, data mining has grown rapidly in visibility and importance within information processing and decision analysis. This is par- ticularly true in the realm of e-commerce, where data mining is moving from a "nice-to-have" to a "must-have" status. In a different though related context, a new computing methodology called granular computing is emerging as a powerful tool for the conception, analysis and design of information/intelligent systems. In essence, data mining deals with summarization of information which is resident in large data sets, while granular computing plays a key role in the summarization process by draw- ing together points (objects) which are related through similarity, proximity or functionality. In this perspective, granular computing has a position of centrality in data mining. Another methodology which has high relevance to data mining and plays a central role in this volume is that of rough set theory. Basically, rough set theory may be viewed as a branch of granular computing. However, its applications to data mining have predated that of granular computing. |
| Illustrations: |
56 Tables, black and white; IX, 537 p. |
| Publication: |
Germany |
| Imprint: |
Physica-Verlag GmbH & Co |
| Returns: |
Returnable |
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