Study on Consumer Behavior Predict in E-commerce Based on Multi-Agent

This paper adopted the method of user interest concept tree based on domain ontology, and proposed a multi-agent based consumer behavior forecasting model in e-commerce to overcome the limitations of traditional consumer behavior forecasting method. The model consists of multiple agents. They are consumer behavior forecast agent, user interest model management agent, monitoring agent and source data monitoring agent. These agents collaborate with each other and then predict consumer behavior. In order to validate the feasibility of the model, the paper combined with the artificial intelligence technology, the database technology, the networkings as well as the electronic commerce correlation technique to build e-commerce consumer behavior predict expert system. From the test results, compared with the original method, it can effectively analyze and predict e-commerce customers consumer behavior, and can be concluded that the customer's overall consumption trend.