Data Mining, Rough Sets and Granular Computing / Studies in Fuzziness and Soft Computing Bd.95 (PDF)
(Sprache: Englisch)
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...
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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.
Bibliographische Angaben
- 2013, 2002, 537 Seiten, Englisch
- Herausgegeben: Tsau Young Lin, Yiyu Y. Yao, Lotfi A. Zadeh
- Verlag: Physica-Verlag HD
- ISBN-10: 3790817910
- ISBN-13: 9783790817911
- Erscheinungsdatum: 11.11.2013
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
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