Granular Relational Data Mining

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Granular Relational Data Mining

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Author : Piotr Hońko
language : en
Publisher: Springer
Release Date : 2017-02-03

Granular Relational Data Mining written by Piotr Hońko and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-03 with Technology & Engineering categories.

This book provides two general granular computing approaches to mining relational data, the first of which uses abstract descriptions of relational objects to build their granular representation, while the second extends existing granular data mining solutions to a relational case. Both approaches make it possible to perform and improve popular data mining tasks such as classification, clustering, and association discovery. How can different relational data mining tasks best be unified? How can the construction process of relational patterns be simplified? How can richer knowledge from relational data be discovered? All these questions can be answered in the same way: by mining relational data in the paradigm of granular computing! This book will allow readers with previous experience in the field of relational data mining to discover the many benefits of its granular perspective. In turn, those readers familiar with the paradigm of granular computing will find valuable insights on its application to mining relational data. Lastly, the book offers all readers interested in computational intelligence in the broader sense the opportunity to deepen their understanding of the newly emerging field granular-relational data mining.

Data Mining Rough Sets And Granular Computing

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Author : Tsau Young Lin
language : en
Publisher: Springer Science & Business Media
Release Date : 2002-04-10

Data Mining Rough Sets And Granular Computing written by Tsau Young Lin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-04-10 with Computers categories.

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.

Time Granularities In Databases Data Mining And Temporal Reasoning

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Author : Claudio Bettini
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29

Time Granularities In Databases Data Mining And Temporal Reasoning written by Claudio Bettini and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Computers categories.

Calendar and time units and specialized units, such as business days and academic years, play a major role in a wide range of information system applications. System support for reasoning about these units, called granularities, is important for the efficient design, use, and implementation of such applications. This book deals with several aspects of temporal information and provides a unifying model for granularities. Practitioners can learn about critical aspects that must be taken into account when designing and implementing databases supporting temporal information.

Relational Data Mining

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Author : Saso Dzeroski
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17

Relational Data Mining written by Saso Dzeroski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Computers categories.

As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area. The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining. This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.

Data Mining Rough Sets And Granular Computing

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Author : Tsau Young Lin
language : en
Publisher:
Release Date : 2014-01-15

Data Mining Rough Sets And Granular Computing written by Tsau Young Lin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.

Data Mining Rough Sets And Granular Computing

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Author : Tsau Young Lin
language : en
Publisher: Physica
Release Date : 2013-11-11

Data Mining Rough Sets And Granular Computing written by Tsau Young Lin and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Computers categories.

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 Sets Fuzzy Sets Data Mining And Granular Computing

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Author : Dominik Slezak
language : en
Publisher: Springer
Release Date : 2005-09-19

Rough Sets Fuzzy Sets Data Mining And Granular Computing written by Dominik Slezak and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-09-19 with Computers categories.

This volume contains the papers selected for presentation at the 10th Int- national Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005, organized at the University of Regina, August 31st–September 3rd, 2005. This conference followed in the footsteps of inter- tional events devoted to the subject of rough sets, held so far in Canada, China, Japan,Poland,Sweden, and the USA. RSFDGrC achievedthe status of biennial international conference, starting from 2003 in Chongqing, China. The theory of rough sets, proposed by Zdzis law Pawlak in 1982, is a model of approximate reasoning. The main idea is based on indiscernibility relations that describe indistinguishability of objects. Concepts are represented by - proximations. In applications, rough set methodology focuses on approximate representation of knowledge derivable from data. It leads to signi?cant results in many areas such as ?nance, industry, multimedia, and medicine. The RSFDGrC conferences put an emphasis on connections between rough sets and fuzzy sets, granularcomputing, and knowledge discoveryand data m- ing, both at the level of theoretical foundations and real-life applications. In the case of this event, additional e?ort was made to establish a linkage towards a broader range of applications. We achieved it by including in the conference program the workshops on bioinformatics, security engineering, and embedded systems, as well as tutorials and sessions related to other application areas.

Rough Sets Fuzzy Sets Data Mining And Granular Computing

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Author : Guoyin Wang
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-05-08

Rough Sets Fuzzy Sets Data Mining And Granular Computing written by Guoyin Wang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-05-08 with Computers categories.

This book constitutes the refereed proceedings of the 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2003, held in Chongqing, China in May 2003. The 39 revised full papers and 75 revised short papers presented together with 2 invited keynote papers and 11 invited plenary papers were carefully reviewed and selected from a total of 245 submissions. The papers are organized in topical sections on rough sets foundations and methods; fuzzy sets and systems; granular computing; neural networks and evolutionary computing; data mining, machine learning, and pattern recognition; logics and reasoning; multi-agent systems; and Web intelligence and intelligent systems.

Multi Relational Data Mining

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Author : Arno J. Knobbe
language : en
Publisher:
Release Date : 1999

Multi Relational Data Mining written by Arno J. Knobbe and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with categories.

Rough Granular Computing In Knowledge Discovery And Data Mining

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Author : J. Stepaniuk
language : en
Publisher: Springer
Release Date : 2009-01-29

Rough Granular Computing In Knowledge Discovery And Data Mining written by J. Stepaniuk and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-29 with Computers categories.

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.