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Fuzzy Sets in Information Retrieval and Cluster Analysis - S. Miyamoto
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S. Miyamoto:
Fuzzy Sets in Information Retrieval and Cluster Analysis - nieuw boek

ISBN: 9789048140671

ID: 978904814067

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. S. Miyamoto, Books, Fuzzy Sets in Information Retrieval and Cluster Analysis Books, Springer-Verlag/Sci-Tech/Trade

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Fuzzy Sets in Information Retrieval and Cluster Analysis - Miyamoto, S.
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Miyamoto, S.:
Fuzzy Sets in Information Retrieval and Cluster Analysis - pocketboek

2010, ISBN: 9789048140671

[ED: Softcover], [PU: Springer Netherlands], 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. 2010. x, 264 S. 240 mm Versandfertig in 3-5 Tagen, DE, [SC: 0.00], Neuware, gewerbliches Angebot, offene Rechnung (Vorkasse vorbehalten)

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Fuzzy Sets in Information Retrieval and Cluster Analysis - S. Miyamoto
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S. Miyamoto:
Fuzzy Sets in Information Retrieval and Cluster Analysis - gebruikt boek

ISBN: 9048140676

ID: 10928997

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. computers,computers and technology,language arts,math,mathematics,science and math Mathematics, Springer

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Fuzzy Sets in Information Retrieval and Cluster Analysis - S. Miyamoto
uitverkocht boek
(*)
S. Miyamoto:
Fuzzy Sets in Information Retrieval and Cluster Analysis - gebruikt boek

ISBN: 9048140676

ID: 10928997

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. computers,computers and technology,math,mathematics,science and math Mathematics, Springer

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Fuzzy Sets in Information Retrieval and Cluster Analysis - Sadaaki Miyamoto
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Sadaaki Miyamoto:
Fuzzy Sets in Information Retrieval and Cluster Analysis - pocketboek

2010, ISBN: 9789048140671

gebonden uitgave, ID: 14930169

Softcover reprint of hardcover 1st ed. 1990, Softcover, Buch, [PU: Springer]

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EAN (ISBN-13): 9789048140671
ISBN (ISBN-10): 9048140676
Gebonden uitgave
pocket book
Verschijningsjaar: 2010
Uitgever: Springer-Verlag GmbH
272 Bladzijden
Gewicht: 0,415 kg
Taal: eng/Englisch

Boek bevindt zich in het datenbestand sinds 13.08.2011 14:07:05
Boek voor het laatst gevonden op 08.09.2018 22:36:06
ISBN/EAN: 9789048140671

ISBN - alternatieve schrijfwijzen:
90-481-4067-6, 978-90-481-4067-1


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