Data Mining, Rough Sets and Granular Computing

Data Mining, Rough Sets and Granular Computing PDF

Author: Tsau Young Lin

Publisher: Physica

Published: 2013-11-11

Total Pages: 538

ISBN-13: 3790817910

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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.

Data Mining, Rough Sets and Granular Computing

Data Mining, Rough Sets and Granular Computing PDF

Author: Tsau Young Lin

Publisher: Springer Science & Business Media

Published: 2002-04-10

Total Pages: 556

ISBN-13: 9783790814613

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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.

Rough – Granular Computing in Knowledge Discovery and Data Mining

Rough – Granular Computing in Knowledge Discovery and Data Mining PDF

Author: J. Stepaniuk

Publisher: Springer Science & Business Media

Published: 2008-08-19

Total Pages: 162

ISBN-13: 3540708006

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This book covers methods based on a combination of granular computing, rough sets, and knowledge discovery in data mining (KDD). The discussion of KDD foundations based on the rough set approach and granular computing feature illustrative applications.

Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing

Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing PDF

Author: Guoyin Wang

Publisher: Springer

Published: 2003-08-03

Total Pages: 746

ISBN-13: 354039205X

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This volume contains the papers selected for presentation at the 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2003) held at Chongqing University of Posts and Telecommunications, Chongqing, P.R. China, May 26–29, 2003. There were 245 submissions for RSFDGrC 2003 excluding for 2 invited keynote papers and 11 invited plenary papers. Apart from the 13 invited papers, 114 papers were accepted for RSFDGrC 2003 and were included in this volume. The acceptance rate was only 46.5%. These papers were divided into 39 regular oral presentation papers (each allotted 8 pages), 47 short oral presentation papers (each allotted 4 pages) and 28 poster presentation papers (each allotted 4 pages) on the basis of reviewer evaluations. Each paper was reviewed by three referees. The conference is a continuation and expansion of the International Workshops on Rough Set Theory and Applications. In particular, this was the ninth meeting in the series and the first international conference. The aim of RSFDGrC2003 was to bring together researchers from diverse fields of expertise in order to facilitate mutual understanding and cooperation and to help in cooperative work aimed at new hybrid paradigms. It is our great pleasure to dedicate this volume to Prof. Zdzislaw Pawlak, who first introduced the basic ideas and definitions of rough sets theory over 20 years ago.

Rough Set Theory and Granular Computing

Rough Set Theory and Granular Computing PDF

Author: Masahiro Inuiguchi

Publisher: Springer

Published: 2012-12-06

Total Pages: 303

ISBN-13: 3540364730

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After 20 years of pursuing rough set theory and its applications a look on its present state and further prospects is badly needed. The monograph Rough Set Theory and Granular Computing edited by Masahiro Inuiguchi, Shoji Hirano and Shusaku Tsumoto meets this demand. It presents the newest developments in this area and gives fair picture of the state of the art in this domain. Firstly, in the keynote papers by Zdzislaw Pawlak, Andrzej Skowron and Sankar K. Pal the relationship of rough sets with other important methods of data analysis -Bayes theorem, neuro computing and pattern recognitio- is thoroughly examined. Next, several interesting generalizations of the the ory and new directions of research are presented. Furthermore application of rough sets in data mining, in particular, rule induction methods based on rough set theory is presented and discussed. Further important issue dis cussed in the monograph is rough set based data analysis, including study of decisions making in conflict situations. Last but not least, some recent engi neering applications of rough set theory are given. They include a proposal of rough set processor architecture organization for fast implementation of ba sic rough set operations and discussion of results concerning advanced image processing for unmanned aerial vehicle. Thus the monograph beside presenting wide spectrum of ongoing research in this area also points out new emerging areas of study and applications, which makes it a valuable source of information to all interested in this do main.

Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing

Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing PDF

Author: Yiyu Yao

Publisher: Springer

Published: 2015-11-21

Total Pages: 505

ISBN-13: 3319257838

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This book constitutes the refereed conference proceedings of the 15th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2015, held in Tianjin, China in November 2015 as one of the co-located conference of the 2015 Joint Rough Set Symposium, JRS 2015. The 44 papers were carefully reviewed and selected from 97 submissions. The papers in this volume cover topics such as rough sets: the experts speak; generalized rough sets; rough sets and graphs; rough and fuzzy hybridization; granular computing; data mining and machine learning; three-way decisions; IJCRS 2015 data challenge.

Rough – Granular Computing in Knowledge Discovery and Data Mining

Rough – Granular Computing in Knowledge Discovery and Data Mining PDF

Author: J. Stepaniuk

Publisher: Springer

Published: 2009-01-29

Total Pages: 162

ISBN-13: 3540708014

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This book covers methods based on a combination of granular computing, rough sets, and knowledge discovery in data mining (KDD). The discussion of KDD foundations based on the rough set approach and granular computing feature illustrative applications.

Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing

Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing PDF

Author: Davide Ciucci

Publisher: Springer

Published: 2013-10-07

Total Pages: 412

ISBN-13: 3642412181

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This book constitutes the thoroughly refereed conference proceedings of the 14th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2013, held in Halifax, Canada in October 2013 as one of the co-located conference of the 2013 Joint Rough Set Symposium, JRS 2013. The 69 papers (including 44 regular and 25 short papers) included in the JRS proceedings (LNCS 8170 and LNCS 8171) were carefully reviewed and selected from 106 submissions. The papers in this volume cover topics such as inconsistency, incompleteness, non-determinism; fuzzy and rough hybridization; granular computing and covering-based rough sets; soft clustering; image and medical data analysis.

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