Könyv Fuzzy Sets in Information Retrieval and Cluster Analysis S. Miyamoto

Fuzzy Sets in Information Retrieval and Cluster Analysis

Szerző: S. Miyamoto
Nyelv: Angol
Kötés: Kemény kötésű
Kiadó: Springer
Elérhetőség: Beszállítói készleten
Küldés 10-13 napon belül
59 739 Ft
The present monograph intends to establish a solid link among three fields: fuzzy set theory, inform...

Információk a könyvről

Szerző
Nyelv
Angol
Kötés
Könyv - Kemény kötésű
Kiadva
1990
oldal
264
EAN
9780792307211
ISBN
0792307216
Enbook ID
01392968
Kiadó
Súly
1250
Méretek
156 x 234 x 19

Teljes leírás

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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