Current electronic commerce recommendation system is designed for single electronic commerce website and current recommendation technologies have obvious deficiencies Centralized recommendation systems can not resolve the contradiction between high recommendation quality and timely response, as well as that between limited recommendation range and ever rich information on the web. Distributed recommendation systems are expected to improve the recommendation quality while maintaining high performance. This paper analyses the problems of traditional electronic commerce recommendation system and clarifies the advantage of applying grid technology into electronic commerce recommendation system. It discusses the prototype of an intelligent recommendation system, namely grid based electronic commerce recommendation system (GBECRS). The paper analyses rationale and mechanism of GBECRS and designs its logical structure. It focuses on the design of grid services which are needed to be deployed into electronic commerce recommendation grid. Finally it does deep analysis of key technologies that are applied in the system.

With the emergence of the e-Catalog, there has been an increasingly wide application of commodities query in distributed environment in the field of e-commerce. But e-Catalog is often autonomous and heterogeneous, effectively integrating and querying them is a delicate and time-consuming task. Electronic catalog contains rich semantics associated with products, and serves as a challenging domain for ontology application. Ontology is concerned with the nature and relations of being. It can play a crucial role in e-commerce as a formalization of e-Catalog. User personalized catalog ontology aims at capturing the users' interests in a working domain, which forms the basis of providing personalized e-Catalog services. In this paper, we present an ontological model of e-Catalogs, and design a semantic personalized e-Catalog service system (SPECSS), which achieves match user personalized catalog ontology (UPCO) and domain e-Catalog ontology (DECO) based on ontology integrated and focus on four key technologies: user personalized catalog ontology generation, domain and local e-Catalog construction, semantic match between them and e-Catalog semantic query system based on heterogeneous catalog database.

The manual construction of e-Catalog ontologies which involves the acquisition, conceptualization, evaluation and formalization of domaindependent knowledge, has been largely identified as a costly, time-consuming, tedious and error prone task. In this paper, we provide a method of customer-oriented eCatalog ontology automatic construction, by acquiring concept sets, identifying properties, learning relations and extracting individuals based on meta model and international classification standards and e-commerce web.

In e-commerce environment, trading partners exchange product information in the form of e-catalogs. With the rapid developing of e-commerce and the increasing in the number of goods online, the e-catalogs accordingly become very large. As the result of the catalog in massive sites, not only customers are dazzling, but also business services are affected. At the same time, the main electronic catalog enquiring service-based on keywords also exist the problems that customers can not enquiry similar semantic and the related semantic goods and many other issues. For the customers, it is difficult to simply use keywords to faithfully express their real needs of goods. These issues make customers can not quickly and accurately gain results, and also reduce the company's management efficiency and profit-effective from the massive electronic catalog of product website.Electronic catalog contains rich semantics associated with products, and serves as a challenging domain for ontology application. Ontology is concerned with the nature and relations of being. It can play a crucial role in e-commerce as a formalization of e-Catalogs. In this paper, we present an ontological model of e-Catalogs, and design a semantic querying system based on e-catalog ontology (SQSEO).