| 书目名称 | Fuzzy Sets in Information Retrieval and Cluster Analysis | | 编辑 | Sadaaki Miyamoto | | 视频video | | | 丛书名称 | Theory and Decision Library D: | | 图书封面 |  | | 描述 | 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, t | | 出版日期 | Book 1990 | | 关键词 | Algebra; algorithm; algorithms; calculus; document; fuzzy; fuzzy set; model; system | | 版次 | 1 | | doi | https://doi.org/10.1007/978-94-015-7887-5 | | isbn_softcover | 978-90-481-4067-1 | | isbn_ebook | 978-94-015-7887-5 | | copyright | Springer Science+Business Media B.V. 1990 |
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发表于 2025-3-21 19:45:54
