Personal Document Recommendation System Based on Data Mining Techniques
Shu-Ming Hsieh, Sun-Jen Huang, Chiun‐Chieh Hsu, Hong‐Chan Chang · Web Intelligence · 2004
Most existing recommendation systems may not be very effective due to the lack of the adequate knowledge of user's behavior or interests. Some systems are not] efficient enough because of the huge on-line computational demand. In this paper, we propose a personal documents recommendation system that effectively filters the on-line news on WWW for each individual user. The proposed system recommends useful news by employing the profiling techniques of modified content- and collaborative-based filtering. In order to reduce the on-line computation and improve the recommendation quality, we design a tree-based data mining algorithm that treats users' behavior and interest as input and filter the news documents efficiently.