The Study Of The Theory And Methodology Of Intelligent Electronic Commerce Recommendation Based On Knowledge Grid

Current recommender systems cannot meet the demand of large-scale electroniccommerce in the distributed environment. The knowledge engineering, semantic webtechnologies and electronic recommendation technologies together can be exploited torealize the effective acquisition and fusion of the knowledge of products, userrequirements and recommendation function, and can further realize the synergizedcollaboration of constituents of the recommender systems in the grid environment.This dissertation researches on the basic theory and methodology of intelligentelectronic commerce recommendation based on the knowledge grid which we hopewill provide the fundamental support in theory and methodology for developinghighly responsive and effective recommender systems for large-scale electroniccommerce in distributed environments.The research on the theory and methodology is subdivided into three levelswhich are correlated with each other closely to support distributed recommendationfor large-scale electronic commerce. The first is the theory and methodology ofknowledge-driven intelligent electronic commerce recommender systems. The secondis the theory and methodology of intelligent electronic commerce recommendationknowledge grid (IECRKG). The third is the theory and methodology of the IECRKGservice communities.In chapter 2 the relative theories are introduced which include the basic theory ofthe semantic web, current developments in grid technologies, the theories,methodologies and technologies for semantic grid and knowledge grid, the conceptand main technologies of electronic commerce recommender systems and theconcerned data mining technologies.In chapter 3 the theory and methodology of knowledge-based intelligentelectronic commerce recommender systems are proposed. Firstly how to represent theknowledge in recommender systems uniformly is explored based on the constructionof RecommendOnto, the ontology for the domain of electronic commercerecommendation. After the general analysis of the methods of acquiring knowledge inrecommender systems, the methods of acquiring knowledge of products and userrequirements are elaborated. The mechanisms of ontology reasoning, rule reasoningand case based reasoning are discussed. The method of generating recommendationresults is also discussed by adopting the proposed algorithm of semantic similarityand entropy of commodities' features. Finally the self-adaptive algorithm of choosingrecommendation techniques in recommender systems is analyzed. In chapter 4 the hierarchical model and service oriented architecture of IECRKGare designed. After that the resource space model, the uniform representation ofresource, and the IECRKG resource operation language are proposed. Then the keytechnologies concerned with the semantic interaction, especially the semantics basedservice matching and knowledge based workflow, are explored. Finally how toimplement knowledge search service, knowledge discovery service and knowledgefusion service is discussed.In chapter 5 the problems of how to organize and optimize the communities onIECRKG are tackled. The main work includes: the principle and structure of thecommunities, the organizing and formalizing mechanism of the communities, the keyrouting algorithms, and the algorithms of self organized optimization.