WebSail: From On-Line Learning to Web Search

In this paper we report our research on building WebSail { an intelligent web search engine that is able to perform real-time adaptive learning. WebSail learns from the user's relevance feedback, so that it is able to speed up its search process and to enhance its search performance. We design an e cient adaptive learning algorithm TW2 to search for web documents. WebSail employs TW2 together with an internal index database and a real-time meta-searcher to perform real-time adaptive learning to nd desired documents with as little relevance feedback from the user as possible. The architecture and performance of WebSail are also discussed.

• Type: Conference
• Year: 2000
• Where: WISE
• Authors: Zhixiang Chen, Xiannong Meng, Binhai Zhu, Richard H. Fowler
• Keywords: Adaptive Learning, Internet Technology, Real-time Adaptive Learning, Relevance Feedback, WISE 2000