Rough Set in Knowledge Representation and Granular Computing | On Some Aspects

D. P. Acharjya

ISBN 10: 3659160849 ISBN 13: 9783659160844
Editorial: LAP Lambert Academic Publishing, 2012
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Rough Set in Knowledge Representation and Granular Computing | On Some Aspects | D. P. Acharjya | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659160844 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de ref. del artículo 106392364

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Knowledge representation and granular computing is an active area of current research for their potential application to many real life problems. Thus, it is challenging for human being in converting huge data into knowledge, and to use this knowledge to make informed decisions properly. It is very difficult to extract expert knowledge from the universe and is an active area of research in artificial intelligence. This involves analysis of how to accurately and effectively use a set of symbols to represent a set of facts within a knowledge domain. The focus of the work in this book is a combination of theoretical advancements of some of the extended models and their applications in knowledge bases. The theoretical advancements have been supported with formal proof to establish soundness whereas the applications are mostly undertaken from real life situations. The book discusses some aspects of rough sets approach in the study of knowledge discovery in databases and granular computing. An elaborate bibliography is provided at the end of the book. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of knowledge representation.

Reseña del editor: Knowledge representation and granular computing is an active area of current research for their potential application to many real life problems. Thus, it is challenging for human being in converting huge data into knowledge, and to use this knowledge to make informed decisions properly. It is very difficult to extract expert knowledge from the universe and is an active area of research in artificial intelligence. This involves analysis of how to accurately and effectively use a set of symbols to represent a set of facts within a knowledge domain. The focus of the work in this book is a combination of theoretical advancements of some of the extended models and their applications in knowledge bases. The theoretical advancements have been supported with formal proof to establish soundness whereas the applications are mostly undertaken from real life situations. The book discusses some aspects of rough sets approach in the study of knowledge discovery in databases and granular computing. An elaborate bibliography is provided at the end of the book. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of knowledge representation.

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Título: Rough Set in Knowledge Representation and ...
Editorial: LAP Lambert Academic Publishing
Año de publicación: 2012
Encuadernación: Taschenbuch
Condición: Neu

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D. P. Acharjya
Publicado por LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659160849 ISBN 13: 9783659160844
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Acharjya D. P.D P Acharjya received Ph. D in Computer Science from Berhampur University, India. He is an Associate Professor in School of Computing Science and Engineering, VIT University, India. He has authored many journal papers a. Nº de ref. del artículo: 5135964

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Publicado por LAP Lambert Academic Publishing, 2012
ISBN 10: 3659160849 ISBN 13: 9783659160844
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Knowledge representation and granular computing is an active area of current research for their potential application to many real life problems. Thus, it is challenging for human being in converting huge data into knowledge, and to use this knowledge to make informed decisions properly. It is very difficult to extract expert knowledge from the universe and is an active area of research in artificial intelligence. This involves analysis of how to accurately and effectively use a set of symbols to represent a set of facts within a knowledge domain. The focus of the work in this book is a combination of theoretical advancements of some of the extended models and their applications in knowledge bases. The theoretical advancements have been supported with formal proof to establish soundness whereas the applications are mostly undertaken from real life situations. The book discusses some aspects of rough sets approach in the study of knowledge discovery in databases and granular computing. An elaborate bibliography is provided at the end of the book. The material in this book includes concepts, figures, graphs, and tables to guide researchers in the area of knowledge representation. Nº de ref. del artículo: 9783659160844

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