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| Author | : Ewa Orlowska |
| Publisher | : Physica |
| Total Pages | : 615 |
| Release | : 2013-03-14 |
| Genre | : Computers |
| ISBN | : 3790818887 |
Download Incomplete Information: Rough Set Analysis Book in PDF, ePub and Kindle
In 1982, Professor Pawlak published his seminal paper on what he called "rough sets" - a work which opened a new direction in the development of theories of incomplete information. Today, a decade and a half later, the theory of rough sets has evolved into a far-reaching methodology for dealing with a wide variety of issues centering on incompleteness and imprecision of information - issues which playa key role in the conception and design of intelligent information systems. "Incomplete Information: Rough Set Analysis" - or RSA for short - presents an up-to-date and highly authoritative account of the current status of the basic theory, its many extensions and wide-ranging applications. Edited by Professor Ewa Orlowska, one of the leading contributors to the theory of rough sets, RSA is a collection of nineteen well-integrated chapters authored by experts in rough set theory and related fields. A common thread that runs through these chapters ties the concept of incompleteness of information to those of indiscernibility and similarity.
| Author | : Xibei Yang |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 238 |
| Release | : 2012-12-15 |
| Genre | : Computers |
| ISBN | : 3642259359 |
Download Incomplete Information System and Rough Set Theory Book in PDF, ePub and Kindle
"Incomplete Information System and Rough Set Theory: Models and Attribute Reductions" covers theoretical study of generalizations of rough set model in various incomplete information systems. It discusses not only the regular attributes but also the criteria in the incomplete information systems. Based on different types of rough set models, the book presents the practical approaches to compute several reducts in terms of these models. The book is intended for researchers and postgraduate students in machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, and granular computing. Dr. Xibei Yang is a lecturer at the School of Computer Science and Engineering, Jiangsu University of Science and Technology, China; Jingyu Yang is a professor at the School of Computer Science, Nanjing University of Science and Technology, China.
| Author | : Z. Pawlak |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 247 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 9401135347 |
Download Rough Sets Book in PDF, ePub and Kindle
To-date computers are supposed to store and exploit knowledge. At least that is one of the aims of research fields such as Artificial Intelligence and Information Systems. However, the problem is to understand what knowledge means, to find ways of representing knowledge, and to specify automated machineries that can extract useful information from stored knowledge. Knowledge is something people have in their mind, and which they can express through natural language. Knowl edge is acquired not only from books, but also from observations made during experiments; in other words, from data. Changing data into knowledge is not a straightforward task. A set of data is generally disorganized, contains useless details, although it can be incomplete. Knowledge is just the opposite: organized (e.g. laying bare dependencies, or classifications), but expressed by means of a poorer language, i.e. pervaded by imprecision or even vagueness, and assuming a level of granularity. One may say that knowledge is summarized and organized data - at least the kind of knowledge that computers can store.
| Author | : Jian Yu |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 797 |
| Release | : 2010-09-27 |
| Genre | : Computers |
| ISBN | : 3642162479 |
Download Rough Set and Knowledge Technology Book in PDF, ePub and Kindle
This book constitutes the refereed proceedings of the 5th International Conference on Rough Set and Knowledge Technology, RSKT 2010, held in Beijing, China, in October 2010. The 98 revised full papers papers presented were carefully reviewed and selected from 175 initial submissions. The papers are organized in topical sections on rough sets and computing theory, fuzzy sets, knowledge technology, intelligent information processing, health informatics and biometrics authentication, neural networks, complex networks, granular computing, metaheuristic, cloud model and its application, data mining in cloud computing, decision-theoretic rough set model, and quotient space theory research and application.
| Author | : Guoyin Wang |
| Publisher | : Springer |
| Total Pages | : 439 |
| Release | : 2017-04-28 |
| Genre | : Technology & Engineering |
| ISBN | : 3319549669 |
Download Thriving Rough Sets Book in PDF, ePub and Kindle
This special book is dedicated to the memory of Professor Zdzisław Pawlak, the father of rough set theory, in order to commemorate both the 10th anniversary of his passing and 35 years of rough set theory. The book consists of 20 chapters distributed into four sections, which focus in turn on a historical review of Professor Zdzisław Pawlak and rough set theory; a review of the theory of rough sets; the state of the art of rough set theory; and major developments in rough set based data mining approaches. Apart from Professor Pawlak’s contributions to rough set theory, other areas he was interested in are also included. Moreover, recent theoretical studies and advances in applications are also presented. The book will offer a useful guide for researchers in Knowledge Engineering and Data Mining by suggesting new approaches to solving the problems they encounter.
| Author | : Hassanien, Aboul Ella |
| Publisher | : IGI Global |
| Total Pages | : 314 |
| Release | : 2007-08-31 |
| Genre | : Business & Economics |
| ISBN | : 1599045540 |
Download Rough Computing: Theories, Technologies and Applications Book in PDF, ePub and Kindle
Covers key rough computing research, surveying a full range of topics and examining defining issues of the field.
| Author | : James F. Peters |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 414 |
| Release | : 2004-07-05 |
| Genre | : Computers |
| ISBN | : 3540223746 |
Download Transactions on Rough Sets I Book in PDF, ePub and Kindle
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, starting from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. This first volume of the Transactions on Rough Sets opens with an introductory article by Zdzislaw Pawlak, the originator of rough sets. Nine papers deal with rough set theory and eight are devoted to applications in various domains.
| Author | : James F. Peters |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 760 |
| Release | : 2008-12-18 |
| Genre | : Computers |
| ISBN | : 3540898751 |
Download Transactions on Rough Sets IX Book in PDF, ePub and Kindle
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. This book, which constitutes the ninth volume of the Transactions on Rough Sets series, providing evidence of the continuing growth of a number of research streams. It includes articles that are extensions of papers included in the first conference on Rough Sets and Intelligent Systems Paradigms. The 26 papers presented in this volume introduce a number of new advances in the foundations and applications of artificial intelligence, engineering, image processing, logic, mathematics, medicine, music, and science.
| Author | : Lech Polkowski |
| Publisher | : Springer |
| Total Pages | : 581 |
| Release | : 2017-06-22 |
| Genre | : Computers |
| ISBN | : 3319608401 |
Download Rough Sets Book in PDF, ePub and Kindle
This two-volume set LNAI 10313 and LNAI 10314 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2017, held in Olsztyn, Poland, in July 2017. The 74 revised full papers presented together with 16 short papers and 16 invited talks, were carefully reviewed and selected from 130 submissions. The papers in this two set-volume of IJCRS 2017 follow the track already rutted by RSCTC and JRS conferences which aimed at unification of many facets of rough set theory from theoretical aspects of the rough set idea bordering on theory of concepts and going through algebraic structures, topological structures, logics for uncertain reasoning, decision algorithms, relations to other theories of vagueness and ambiguity, then to extensions of the rough set idea like granular structures, rough mereology, and to applications of the idea in diverse fields of applied science including hybrid methods like rough-fuzzy, neuro-rough, neuro-rough-fuzzy computing. IJCRS 2017 encompasses topics spread among four main tracks: Rough Sets and Data Science (in relation to RSCTC series organized since 1998); Rough Sets and Granular Computing (in relation to RSFDGrC series organized since 1999); Rough Sets and Knowledge Technology (in relation to RSKT series organized since 2006); and Rough Sets and Intelligent Systems (in relation to RSEISP series organized since 2007).
| Author | : Lech Polkowski |
| Publisher | : Physica |
| Total Pages | : 679 |
| Release | : 2012-10-07 |
| Genre | : Computers |
| ISBN | : 3790818402 |
Download Rough Set Methods and Applications Book in PDF, ePub and Kindle
Rough set approach to reasoning under uncertainty is based on inducing knowledge representation from data under constraints expressed by discernibility or, more generally, similarity of objects. Knowledge derived by this approach consists of reducts, decision or association rules, dependencies, templates, or classifiers. This monograph presents the state of the art of this area. The reader will find here a deep theoretical discussion of relevant notions and ideas as well as rich inventory of algorithmic and heuristic tools for knowledge discovery by rough set methods. An extensive bibliography will help the reader to get an acquaintance with this rapidly growing area of research.
