Special issue on granular computing and data mining

✍ Scribed by Tsau Y. Lin; Lotfi A. Zadeh

• Publisher: John Wiley and Sons
• Year: 2004
• Tongue: English
• Weight: 29 KB
• Volume: 19
• Category: Article
• ISSN: 0884-8173
• DOI: 10.1002/int.20011

✦ Synopsis

The program of the 2002 World Congress on Computational Intelligence (WCCI 2002) included six sessions on "Granular Computing and Data Mining," reflecting the growing interest in application of granular computing to data mining. In these sessions, a broad range of issues were addressed. This Special Issue is based on papers presented in the sessions on Granular Computing and Data Mining.

In the mid-nineties, L. A. Zadeh initiated a new direction in computing and data analysis which he referred to as granular mathematics. During his sabbatical leave (1996 -1997) at Berkeley, T. Y. Lin focused on a subset of granular mathematics which he called granular computing. To stimulate research on granular computing, a special interest group, with T. Y. Lin as its Chair, was formed within Berkeley Initiative in Soft Computing (BISC). Since then, granular computing has evolved into an active research area, generating many articles, books and presentations at conferences, workshops and special sessions.

The principal focus of attention in the Special Issue is data mining. In essence, data mining may be viewed as a form of summarization of very large datasets, while granular computing may be viewed as operations on summaries of small datasets. The common rule of summarization in data mining and granular computing is the principal reason why granular computing is of high relevance to data mining.

The papers selected for the Special Issue are the following,