Data Mining, Rough Sets and Granular Computing:
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 diffe...
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Heidelberg
Physica-Verlag HD
2002
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| Schriftenreihe: | Studies in Fuzziness and Soft Computing
95 |
| Schlagworte: | |
| Online-Zugang: | FHI01 BTU01 Volltext |
| Zusammenfassung: | 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 |
| Beschreibung: | 1 Online-Ressource (IX, 537 p) |
| ISBN: | 9783790817911 |
| DOI: | 10.1007/978-3-7908-1791-1 |
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| spelling | Data Mining, Rough Sets and Granular Computing edited by Tsau Young Lin, Yiyu Y. Yao, Lotfi A. Zadeh Heidelberg Physica-Verlag HD 2002 1 Online-Ressource (IX, 537 p) txt rdacontent c rdamedia cr rdacarrier Studies in Fuzziness and Soft Computing 95 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 Computer Science Artificial Intelligence (incl. Robotics) Database Management Computer science Database management Artificial intelligence Granular Computing (DE-588)4661337-7 gnd rswk-swf Grobmenge (DE-588)4362502-2 gnd rswk-swf Data Mining (DE-588)4428654-5 gnd rswk-swf 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Granular Computing (DE-588)4661337-7 s 2\p DE-604 Data Mining (DE-588)4428654-5 s 3\p DE-604 Grobmenge (DE-588)4362502-2 s 4\p DE-604 Lin, Tsau Young edt Yao, Yiyu Y. edt Zadeh, Lotfi A. edt Erscheint auch als Druck-Ausgabe 9783790825084 https://doi.org/10.1007/978-3-7908-1791-1 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 4\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Data Mining, Rough Sets and Granular Computing Computer Science Artificial Intelligence (incl. Robotics) Database Management Computer science Database management Artificial intelligence Granular Computing (DE-588)4661337-7 gnd Grobmenge (DE-588)4362502-2 gnd Data Mining (DE-588)4428654-5 gnd |
| subject_GND | (DE-588)4661337-7 (DE-588)4362502-2 (DE-588)4428654-5 (DE-588)4143413-4 |
| title | Data Mining, Rough Sets and Granular Computing |
| title_auth | Data Mining, Rough Sets and Granular Computing |
| title_exact_search | Data Mining, Rough Sets and Granular Computing |
| title_full | Data Mining, Rough Sets and Granular Computing edited by Tsau Young Lin, Yiyu Y. Yao, Lotfi A. Zadeh |
| title_fullStr | Data Mining, Rough Sets and Granular Computing edited by Tsau Young Lin, Yiyu Y. Yao, Lotfi A. Zadeh |
| title_full_unstemmed | Data Mining, Rough Sets and Granular Computing edited by Tsau Young Lin, Yiyu Y. Yao, Lotfi A. Zadeh |
| title_short | Data Mining, Rough Sets and Granular Computing |
| title_sort | data mining rough sets and granular computing |
| topic | Computer Science Artificial Intelligence (incl. Robotics) Database Management Computer science Database management Artificial intelligence Granular Computing (DE-588)4661337-7 gnd Grobmenge (DE-588)4362502-2 gnd Data Mining (DE-588)4428654-5 gnd |
| topic_facet | Computer Science Artificial Intelligence (incl. Robotics) Database Management Computer science Database management Artificial intelligence Granular Computing Grobmenge Data Mining Aufsatzsammlung |
| url | https://doi.org/10.1007/978-3-7908-1791-1 |
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