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Fuzzy Sets in Information Retrieval and Cluster Analysis: 4 (Theory and Decision Library D:) - Tapa dura
Sinopsis
The present monograph intends to establish a solid link among three fields: fuzzy set theory, information retrieval, and cluster analysis. Fuzzy set theory supplies new concepts and methods for the other two fields, and provides a common frame work within which they can be reorganized. Four principal groups of readers are assumed: researchers or students who are interested in (a) application of fuzzy sets, (b) theory of information retrieval or bibliographic databases, (c) hierarchical clustering, and (d) application of methods in systems science. Readers in group (a) may notice that the fuzzy set theory used here is very simple, since only finite sets are dealt with. This simplification enables the max min algebra to deal with fuzzy relations and matrices as equivalent entities. Fuzzy graphs are also used for describing theoretical properties of fuzzy relations. This assumption of finite sets is sufficient for applying fuzzy sets to information retrieval and cluster analysis. This means that little theory, beyond the basic theory of fuzzy sets, is required. Although readers in group (b) with little background in the theory of fuzzy sets may have difficulty with a few sections, they will also find enough in this monograph to support an intuitive grasp of this new concept of fuzzy information retrieval. Chapter 4 provides fuzzy retrieval without the use of mathematical symbols. Also, fuzzy graphs will serve as an aid to the intuitive understanding of fuzzy relations.
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The present monograph intends to establish a solid link among three fields: fuzzy set theory, information retrieval, and cluster analysis. Fuzzy set theory supplies new concepts and methods for the other two fields, and provides a common frame work within which they can be reorganized. Four principal groups of readers are assumed: researchers or students who are interested in (a) application of fuzzy sets, (b) theory of information retrieval or bibliographic databases, (c) hierarchical clustering, and (d) application of methods in systems science. Readers in group (a) may notice that the fuzzy set theory used here is very simple, since only finite sets are dealt with. This simplification enables the max min algebra to deal with fuzzy relations and matrices as equivalent entities. Fuzzy graphs are also used for describing theoretical properties of fuzzy relations. This assumption of finite sets is sufficient for applying fuzzy sets to information retrieval and cluster analysis. This means that little theory, beyond the basic theory of fuzzy sets, is required. Although readers in group (b) with little background in the theory of fuzzy sets may have difficulty with a few sections, they will also find enough in this monograph to support an intuitive grasp of this new concept of fuzzy information retrieval. Chapter 4 provides fuzzy retrieval without the use of mathematical symbols. Also, fuzzy graphs will serve as an aid to the intuitive understanding of fuzzy relations.
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Fuzzy sets in information retrieval and cluster analysis. Theory and decision library Series D System theory, knowledge engineering and problem solving 4; Theory and decision library Series D, System theory, knowledge engineering and problem solving 4.
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Dordrecht, Kluwer, 1990
ISBN 10: 0792307216
ISBN 13: 9780792307211
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Librería: Antiquariat Bookfarm, Löbnitz, Alemania
Calificación del vendedor: 5 de 5 estrellas
Hardcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. C 567 9780792307211 Sprache: Englisch Gewicht in Gramm: 550. Nº de ref. del artículo: 2502951
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Fuzzy Sets in Information Retrieval and Cluster Analysis.
Publicado por
Dordrecht - Boston - London Kluwer Academic Publishers, 1990
ISBN 10: 0792307216
ISBN 13: 9780792307211
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Librería: Antiquariat Fluck, Berlin, Alemania
Calificación del vendedor: 5 de 5 estrellas
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Fuzzy sets in information retrieval and cluster analysis.
Librería: Kloof Booksellers & Scientia Verlag, Amsterdam, Holanda
Calificación del vendedor: 4 de 5 estrellas
Condición: as new. Dordrecht : Kluwer Academic Publishers, 1990. Hardcover. x, 259 pp. illustrations ; 25 cm. (Theory and decision library. Series D, System theory, knowledge engineering and problem solving, 4). Orig. edition. Condition : as new copy. ISBN 9780792307211. Keywords : MATHEMATICS, Nº de ref. del artículo: 263700
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Fuzzy Sets in Information Retrieval and Cluster Analysis
Publicado por
Springer Netherlands, 1990
ISBN 10: 0792307216
ISBN 13: 9780792307211
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Librería: Buchpark, Trebbin, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: Sehr gut. Zustand: Sehr gut | Seiten: 276 | Sprache: Englisch | Produktart: Bücher. Nº de ref. del artículo: 1658116/202
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Fuzzy Sets in Information Retrieval and Cluster Analysis
Librería: moluna, Greven, Alemania
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Gebunden. Condición: New. Nº de ref. del artículo: 5965972
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Fuzzy Sets in Information Retrieval and Cluster Analysis (Theory and Decision Library D:, 4)
Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Condición: New. In. Nº de ref. del artículo: ria9780792307211_new
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Fuzzy Sets in Information Retrieval and Cluster Analysis
Publicado por
Springer Netherlands Mai 1990, 1990
ISBN 10: 0792307216
ISBN 13: 9780792307211
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The present monograph intends to establish a solid link among three fields: fuzzy set theory, information retrieval, and cluster analysis. Fuzzy set theory supplies new concepts and methods for the other two fields, and provides a common frame work within which they can be reorganized. Four principal groups of readers are assumed: researchers or students who are interested in (a) application of fuzzy sets, (b) theory of information retrieval or bibliographic databases, (c) hierarchical clustering, and (d) application of methods in systems science. Readers in group (a) may notice that the fuzzy set theory used here is very simple, since only finite sets are dealt with. This simplification enables the max min algebra to deal with fuzzy relations and matrices as equivalent entities. Fuzzy graphs are also used for describing theoretical properties of fuzzy relations. This assumption of finite sets is sufficient for applying fuzzy sets to information retrieval and cluster analysis. This means that little theory, beyond the basic theory of fuzzy sets, is required. Although readers in group (b) with little background in the theory of fuzzy sets may have difficulty with a few sections, they will also find enough in this monograph to support an intuitive grasp of this new concept of fuzzy information retrieval. Chapter 4 provides fuzzy retrieval without the use of mathematical symbols. Also, fuzzy graphs will serve as an aid to the intuitive understanding of fuzzy relations. 276 pp. Englisch. Nº de ref. del artículo: 9780792307211
Cantidad disponible: 2 disponibles
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Fuzzy Sets in Information Retrieval and Cluster Analysis
Publicado por
Springer Netherlands, Springer Netherlands, 1990
ISBN 10: 0792307216
ISBN 13: 9780792307211
Nuevo
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - The present monograph intends to establish a solid link among three fields: fuzzy set theory, information retrieval, and cluster analysis. Fuzzy set theory supplies new concepts and methods for the other two fields, and provides a common frame work within which they can be reorganized. Four principal groups of readers are assumed: researchers or students who are interested in (a) application of fuzzy sets, (b) theory of information retrieval or bibliographic databases, (c) hierarchical clustering, and (d) application of methods in systems science. Readers in group (a) may notice that the fuzzy set theory used here is very simple, since only finite sets are dealt with. This simplification enables the max min algebra to deal with fuzzy relations and matrices as equivalent entities. Fuzzy graphs are also used for describing theoretical properties of fuzzy relations. This assumption of finite sets is sufficient for applying fuzzy sets to information retrieval and cluster analysis. This means that little theory, beyond the basic theory of fuzzy sets, is required. Although readers in group (b) with little background in the theory of fuzzy sets may have difficulty with a few sections, they will also find enough in this monograph to support an intuitive grasp of this new concept of fuzzy information retrieval. Chapter 4 provides fuzzy retrieval without the use of mathematical symbols. Also, fuzzy graphs will serve as an aid to the intuitive understanding of fuzzy relations. Nº de ref. del artículo: 9780792307211
Cantidad disponible: 1 disponibles
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Fuzzy Sets in Information Retrieval and Cluster Analysis
Publicado por
Springer Netherlands, Springer Netherlands Mai 1990, 1990
ISBN 10: 0792307216
ISBN 13: 9780792307211
Nuevo
Tapa dura
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Buch. Condición: Neu. Neuware -The present monograph intends to establish a solid link among three fields: fuzzy set theory, information retrieval, and cluster analysis. Fuzzy set theory supplies new concepts and methods for the other two fields, and provides a common frame work within which they can be reorganized. Four principal groups of readers are assumed: researchers or students who are interested in (a) application of fuzzy sets, (b) theory of information retrieval or bibliographic databases, (c) hierarchical clustering, and (d) application of methods in systems science. Readers in group (a) may notice that the fuzzy set theory used here is very simple, since only finite sets are dealt with. This simplification enables the max min algebra to deal with fuzzy relations and matrices as equivalent entities. Fuzzy graphs are also used for describing theoretical properties of fuzzy relations. This assumption of finite sets is sufficient for applying fuzzy sets to information retrieval and cluster analysis. This means that little theory, beyond the basic theory of fuzzy sets, is required. Although readers in group (b) with little background in the theory of fuzzy sets may have difficulty with a few sections, they will also find enough in this monograph to support an intuitive grasp of this new concept of fuzzy information retrieval. Chapter 4 provides fuzzy retrieval without the use of mathematical symbols. Also, fuzzy graphs will serve as an aid to the intuitive understanding of fuzzy relations.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 276 pp. Englisch. Nº de ref. del artículo: 9780792307211
Cantidad disponible: 2 disponibles
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Fuzzy Sets in Information Retrieval and Cluster Analysis (Theory and Decision Library D:, 4)
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
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Condición: New. Nº de ref. del artículo: ABLIING23Feb2416190180539
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