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Database discovery using fuzzy sets
Author(s) -
Yager Ronald R.
Publication year - 1996
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/(sici)1098-111x(199609)11:9<691::aid-int7>3.0.co;2-f
Subject(s) - computer science , focus (optics) , fuzzy logic , cluster analysis , set (abstract data type) , domain (mathematical analysis) , information retrieval , fuzzy set , database , knowledge extraction , data mining , artificial intelligence , mathematics , mathematical analysis , physics , optics , programming language
In this work we consider a fuzzy set based approach to the issue of discovery in databases (database mining). The concept of linguistic summaries is described and shown to be a user friendly way to present information contained in a database. We discuss methods for measuring the amount of information provided by a linguistic summary. The issue of conjecturing, how to decide on which summaries may be informative, is discussed. We suggest two approaches to help us focus on relevant summaries. The first method, called the template method, makes use of linguistic concepts related to the domain of the attributes involved in the summaries. The second approach uses the mountain clustering method to help focus our summaries. © 1996 John Wiley & Sons, Inc.