基于模糊关系数据库的聚类算法研究

Analysis for Clustering Algorithms Based on Fuzzy Relational Database

聚类是人类一项最基本的认识活动 ,通过适当的聚类 ,事物才便于研究 ,事物的内部规律才可能为人类所掌握。但是 ,由于人们不总是能对客观世界进行精确的描述 ,很多信息和数据都是不确定的、模糊的。为了处理模糊数据 ,把模糊性引入数据库系统中 ,从而形成了模糊关系数据库。本文对模糊关系数据库下的基于距离函数的聚类算法进行了研究 。

Clustering is one of the fundamental cognitive functions of human being. Proper clustering makes it easier to analyze objects, so the internal rules are more likely to be mastered by mankind. Information and data are often uncertain and obscure, however, from the fact that the nature cannot always be precisely described. Fuzziness is introduced into database systems to process this kind of obscure data, which leads to the emergence of fuzzy relational database. In this paper, clustering algorithms based on distance function for fuzzy relational database are researched, with examples to illustrate how to establish and apply this data-mining model.