User Interesting Collaborative Filtering Model Based on Multi-agent
Hua Wang, Cuiqin Ma, Shaolin Huang, Lizhen Liu · 2009
With the development of internet, web information increases fast, how to filter information which users wanted quickly and accurately is becoming a big problem. But the traditional keyword based search system's recall rate and precision are yet to be improved. Kam-so, the user interesting collaborative filtering model based on multi-agent is put forward. UIFMA uses agent and information filter technology to set up user model and user interesting filter. Experiments show that compared with the traditional search tool, UIFMA has more effective on deducing users' interest and more accuracy in recommending information.