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Data mining and knowledge discovery: A fuzzy set perspective

In: Tatra Mountains Mathematical Publications, vol. 13, no. 4
Witold Pedrycz
Detaily:
Rok, strany: 1997, 195 - 218
O článku:
Knowledge Discovery (KD) and Data mining (DM) are aimed at addressing genuine needs arising from a diversity of data rich and knowledge poor information environments. The role of fuzzy sets in knowledge discovery has been profoundly visible even though fuzzy sets are inherently inclined towards coping with linguistic domain knowledge. The paper re-examines the key issues of knowledge discovery by putting them in the context of the technology of fuzzy sets. Subsequently, we reveal several interesting links between fuzzy data mining and fuzzy sets. The study exploits knowledge-oriented and context based modifications of well known algorithms of fuzzy clustering. We also look at the development of the fuzzy models from the perspective of data mining — a prudent and user — oriented sifting of data, qualitative observations, and calibration of commonsense rules in an attempt to establish meaningful and useful relationships between system's variables.
Ako citovať:
ISO 690:
Pedrycz, W. 1997. Data mining and knowledge discovery: A fuzzy set perspective. In Tatra Mountains Mathematical Publications, vol. 13, no.4, pp. 195-218. 1210-3195.

APA:
Pedrycz, W. (1997). Data mining and knowledge discovery: A fuzzy set perspective. Tatra Mountains Mathematical Publications, 13(4), 195-218. 1210-3195.