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.
