Information Retrieval System Using Fuzzy Logic
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Theoretical Advances and Applications of Fuzzy Logic and Soft Computing
Author: Oscar Castillo
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-10-10
This book comprises a selection of papers on theoretical advances and applications of fuzzy logic and soft computing from the IFSA 2007 World Congress, held in Cancun, Mexico, June 2007. These papers constitute an important contribution to the theory and applications of fuzzy logic and soft computing methodologies.
Fifty Years of Fuzzy Logic and its Applications
This book presents a comprehensive report on the evolution of Fuzzy Logic since its formulation in Lotfi Zadeh’s seminal paper on “fuzzy sets,” published in 1965. In addition, it features a stimulating sampling from the broad field of research and development inspired by Zadeh’s paper. The chapters, written by pioneers and prominent scholars in the field, show how fuzzy sets have been successfully applied to artificial intelligence, control theory, inference, and reasoning. The book also reports on theoretical issues; features recent applications of Fuzzy Logic in the fields of neural networks, clustering, data mining and software testing; and highlights an important paradigm shift caused by Fuzzy Logic in the area of uncertainty management. Conceived by the editors as an academic celebration of the fifty years’ anniversary of the 1965 paper, this work is a must-have for students and researchers willing to get an inspiring picture of the potentialities, limitations, achievements and accomplishments of Fuzzy Logic-based systems.
Fuzzy Sets in Information Retrieval and Cluster Analysis
Author: S. Miyamoto
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
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.