Linguistic Object-Oriented Web Mining

Abstract

The paper proposes a new fuzzy object-oriented web mining algorithm to derive fuzzy knowledge from object data log on web servers. Each web page itself is thought of as a class, and each web page browsed by a client is thought of as an instance. Instances with the same class (web page) may have different quantitative attribute values since they may appear in different clients. The proposed fuzzy mining algorithm can be divided into two main phases. The first phase is called the fuzzy intra-page mining phase, in which the linguistic large itemsets associated with the same classes (pages) but with different attributes are derived. The second phase is called the fuzzy interpage mining phase, in which the large sequences are derived and used to represent the relationship among different web pages. Experimental results also show the effects of the parameters used in the algorithm.