A Design Of WebSite Personality System

Every day, new information, products and services are being offered by providers onthe World Wide Web. At the same time, the number of consumers and the diversity of their interests increase. As a result, providers are seeking ways to infer the customers'interests and to adapt their web sites to make the content of interest more easily accessible. Proposal have suggested Web usage mining as an enabling mechanism to overcome the problem associated with more traditional Web personalization technique such as Collaborative or Content-based filtering.These problems include lack of scalability ,reliance on Subjective user ratings ,and the inability to capture a richer set of semantic relationships among objects.In this paper we present an sequential-pattern-based recommendation System,which extract usage patterns from web log file and use the concept lattice as its data structure storing frequent sequences. Sequential pattern mining, which discovers frequent subsequences as interesting patterns in a sequence database. The Concept Lattice is suitable to discover various knowledge including sequential patterns. Considering the characters of the sequential patterns mining, Fequent Concept Lattice can improve the mining efficiency.