2007 IEEE International Conference on Granular Computing (GRC 2007)
Production and Retrieval of Rough Classes in Multi Relations
San Jose, California
November 02-November 04
ISBN: 0-7695-3032-X
Organizational memory in today's business world forms basis for organizational learning, which is the ability of an organization to gain insight and understanding from experience through experimentation, observation, analysis, and a willingness to examine both successes and failures. This basically requires consideration of different aspects of knowledge that may reside on top of a conventional information management system. Of them, representation, retrieval and production issues of meta patterns constitute to the main theme of this article. Particularly we are interested in a formal approach to handle rough concepts. We utilize rough classifiers to propose a preliminary framework based on minimal term sets with p-norms to extract meta patterns. We describe a relational rule induction approach, which is called rila. Experimental results are provided on the mutagenesis, and the KDD Cup 2001 genes data sets.
Citation:
Mehmet R. Tolun, Hayri Sever, A. Kadir Gorur, "Production and Retrieval of Rough Classes in Multi Relations," grc, pp.192, 2007 IEEE International Conference on Granular Computing (GRC 2007), 2007