Based On The Concept Lattice Web Log Mining And Personal Technology

Every day, new information, products and services are being offered by providers on the 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.Recent proposal have suggested Web usage mining as an enabling mechanism to overcome the problem associated with more traditional Web personalization techniques such as Collaborative or Content-based filtering.These problems include lack of scalability .reliance on Subjective user ratings or static profiles,and the inability to capture a richer set of semantic relationships among objects.Yet,usage-based personalization can be problematic when little usage data is available pertaining to some objects or when the site content changes regularly.For more effective personalization,both usage and content attributes of a site should be integrated into a Web minging framwork and used by the recommendation engine in a uniform manner.In this paper we present an association_ rule-based recommendation System.which extract usage paterns from web log file and use the concept lattice as its data structure storing frequent itemsetSo And we show how to use concept lattice generated to compute a recommendation set for the active user, on real time.Concept lattice's capability of catching the relationship between two sets can be used to get the semantic relationships among page sets based on usage . Another reason we use this structure to our system is its potential ability to integrate the ontology with usage information,for it has an isomorphic structure with recently improved web semantic langusage.