Abstract :
Some challenges for Web site designers are to provide correct and useful information to individual user with different backgrounds and interests, as well as to increase user satisfaction. Most existing Web search tools work only with individual users and do not help a user benefit from previous search experience of others. In this paper, a collaborative Web mining system, collector engine system is presented, a multi-agent system designed to provide post-retrieval analysis and enable across-user collaboration in Web search and mining. This system allows the user to annotate search sessions and share them with other users. The prototype system and component of collector engine system is discussed and described, and especially designs the Web agent, the knowledge discovery of Web agent is extracted based on a combination of Web usage mining and machine learning. The system model is established and realized by J2EE technology. The system´s application shows that subjects´ search performance is degraded, compared to individual search scenarios, in which users have no access to previous searches, when they have access to a limited of earlier search session done by other users
Keywords :
data mining; electronic commerce; information retrieval; learning (artificial intelligence); multi-agent systems; search engines; J2EE technology; Web agent; Web mining tool; collector engine system; e-commerce; knowledge discovery; machine learning; multiagent system; post-retrieval analysis; Collaboration; Collaborative work; Competitive intelligence; Computer architecture; Information retrieval; Machine learning; Search engines; Service oriented architecture; Web mining; Web search;
