The Knowledge Grid Based Intelligent Electronic Commerce Recommender Systems

Abstract

Centralized recommender 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 recommender systems are expected to improve the recommendation quality while maintaining high performance. Large-scale distributed recommendation involves the coordination of various heterogeneous resources which are located on different nodes and need to be represented uniformly and organized normally into the resource space so that a semantically interactive environment can be formed. In this paper the recommendation task is defined as a knowledge based workflow and the knowledge grid is exploited as the platform for knowledge sharing and knowledge service which provides the functions of knowledge discovery, knowledge fusion and knowledge based workflow definition. The rationale of the knowledge grid based intelligent electronic recommender systems (KGBIECRS) is discussed and the service oriented architecture of the knowledge grid is presented. The knowledge grid depends on the semantic grid as the semantically interactive platform to intelligently coordinate the heterogeneous resources on the grid so that the recommendation task submitted by the knowledge grid as a knowledge based workflow can be performed intelligently and adaptively. How to implement the system is also discussed. Finally an example of travel recommendation is given to elaborate the recommendation process.