Rough Sets
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| Author | : Lech Polkowski |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 549 |
| Release | : 2013-06-05 |
| Genre | : Mathematics |
| ISBN | : 3790817767 |
A comprehensive introduction to mathematical structures essential for Rough Set Theory. The book enables the reader to systematically study all topics of rough set theory. After a detailed introduction in Part 1 along with an extensive bibliography of current research papers. Part 2 presents a self-contained study that brings together all the relevant information from respective areas of mathematics and logics. Part 3 provides an overall picture of theoretical developments in rough set theory, covering logical, algebraic, and topological methods. Topics covered include: algebraic theory of approximation spaces, logical and set-theoretical approaches to indiscernibility and functional dependence, topological spaces of rough sets. The final part gives a unique view on mutual relations between fuzzy and rough set theories (rough fuzzy and fuzzy rough sets). Over 300 excercises allow the reader to master the topics considered. The book can be used as a textbook and as a reference work.
| Author | : T.Y. Lin |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 429 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1461314615 |
Rough Sets and Data Mining: Analysis of Imprecise Data is an edited collection of research chapters on the most recent developments in rough set theory and data mining. The chapters in this work cover a range of topics that focus on discovering dependencies among data, and reasoning about vague, uncertain and imprecise information. The authors of these chapters have been careful to include fundamental research with explanations as well as coverage of rough set tools that can be used for mining data bases. The contributing authors consist of some of the leading scholars in the fields of rough sets, data mining, machine learning and other areas of artificial intelligence. Among the list of contributors are Z. Pawlak, J Grzymala-Busse, K. Slowinski, and others. Rough Sets and Data Mining: Analysis of Imprecise Data will be a useful reference work for rough set researchers, data base designers and developers, and for researchers new to the areas of data mining and rough sets.
| Author | : Ajith Abraham |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 330 |
| Release | : 2009-02-26 |
| Genre | : Computers |
| ISBN | : 3540899200 |
Part 1 of this book deals with theoretical contributions of rough set theory, and parts 2 and 3 focus on several real world data mining applications. The book thoroughly explores recent results in rough set research.
| Author | : Ewa Orlowska |
| Publisher | : Physica |
| Total Pages | : 615 |
| Release | : 2013-03-14 |
| Genre | : Computers |
| ISBN | : 3790818887 |
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 | : Z. Pawlak |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 247 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 9401135347 |
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 | : Andrea Campagner |
| Publisher | : Springer Nature |
| Total Pages | : 686 |
| Release | : 2024-01-31 |
| Genre | : Computers |
| ISBN | : 3031509595 |
This book constitutes the refereed proceedings of the International Joint Conference on Rough Sets, IJCRS 2023, held in Krakow, Poland, during October 5–8, 2023. The 43 full papers included in this book were carefully reviewed and selected from 83 submissions. They were organized in topical sections as follows: Rough Set Models, Foundations, Three-way Decisions, Granular Models, Distances and Similarities, Hybrid Approaches, Applications, Cybersecurity and IoT.
| Author | : Hung Son Nguyen |
| Publisher | : Springer |
| Total Pages | : 676 |
| Release | : 2018-08-14 |
| Genre | : Computers |
| ISBN | : 3319993682 |
This LNAI 1103 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2018, held in Quy Nhon, Vietnam, in August 2018. The 40 full papers presented together with 5 short papers were carefully reviewed and selected from 61 submissions. The IJCRS conferences aim at bringing together experts from universities and research centers as well as the industry representing fields of research in which theoretical and applicational aspects of rough set theory already find or may potentially find usage.
| Author | : Wojciech P. Ziarko |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 486 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1447132386 |
The objective of this book is two-fold. Firstly, it is aimed at bringing to gether key research articles concerned with methodologies for knowledge discovery in databases and their applications. Secondly, it also contains articles discussing fundamentals of rough sets and their relationship to fuzzy sets, machine learning, management of uncertainty and systems of logic for formal reasoning about knowledge. Applications of rough sets in different areas such as medicine, logic design, image processing and expert systems are also represented. The articles included in the book are based on selected papers presented at the International Workshop on Rough Sets and Knowledge Discovery held in Banff, Canada in 1993. The primary methodological approach emphasized in the book is the mathematical theory of rough sets, a relatively new branch of mathematics concerned with the modeling and analysis of classification problems with imprecise, uncertain, or incomplete information. The methods of the theory of rough sets have applications in many sub-areas of artificial intelligence including knowledge discovery, machine learning, formal reasoning in the presence of uncertainty, knowledge acquisition, and others. This spectrum of applications is reflected in this book where articles, although centered around knowledge discovery problems, touch a number of related issues. The book is intended to provide an important reference material for students, researchers, and developers working in the areas of knowledge discovery, machine learning, reasoning with uncertainty, adaptive expert systems, and pattern classification.
| Author | : Rafael Bello |
| Publisher | : Springer Nature |
| Total Pages | : 517 |
| Release | : 2020-07-07 |
| Genre | : Computers |
| ISBN | : 3030527050 |
The volume LNAI 12179 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2020, which was due to be held in Havana, Cuba, in June 2020. The conference was held virtually due to the COVID-19 pandemic. The 37 full papers accepted were carefully reviewed and selected from 50 submissions. The papers are grouped in the following topical sections: general rough sets; three-way decision theory; attribute reduction; granular computing; formal concept analysis; data summarization; community detection; fuzzy cognitive maps; tutorials.
| Author | : Dominik Ślęzak |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 760 |
| Release | : 2005 |
| Genre | : Artificial intelligence |
| ISBN | : 3540286608 |
This volume contains the papers selected for presentation at the 10th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005, organized at the University of Regina, August 31st–September 3rd, 2005.
