Summarizing Data Collection Support Using Fuzzy Petri Net

Abstract

With the growth of electronic commerce (EC) on the Internet and the increase of interests in software agents, researches for the automated summarizing collections are proceeding rapidly. A common view about mining is that it is an exercise of clustering customers, markets, products, and other objects of interest in useful ways from large amounts of data. Database summarization is a task that reduces a large number of actual database tuples into a relatively small number of generalized descriptions. Summary discovery provides the user with comprehensive information for grasping the essence of a focused portion from a large amount of information in a database. In this paper, we propose a summary discovery process based on the fuzzy Petri net model to form more generalized tuples. We present a general type of fuzzy Petri net as a representation form of a database summary including fuzzy concepts. By virtue of fuzzy Petri net model where fuzzy set hierarchies in the actual domain are natually expressed, the discovery process yields more accurate database summaries. The proposed method is more efficient due to the concurrent process of summary discovery technique.