Mining User's Interest from Interactive Behaviors in QA System
Zhongying Zhao, Shengzhong Feng, Yongquan Liang, Qingtian Zeng, Jianping Fan · 2009
User interest model, as a key component of user model, is very important for personalized or user adaptive E-learning systems. In this paper, we propose an approach for mining userpsilas interest from interactive behaviors. We also develop and implement a domain-specific interactive QA system oriented to Artificial Intelligence. The course ontology, predefined to describe the skeleton of AI course, is used to generate the structure of our interactive QA system. Students can pose and browse questions and answers on their favorite boards. The interactive behaviors, including whether student has pose a question, browsing and answering times, are considered to compute each studentpsilas interest. The experiment conducted to evaluate the performance of our approach indicates that our method can capture userpsilas interest precisely.