An improvement on expert finding systems by Vector Space model and Query Expansion technic

Due to enormous volume of information available on the Web، finding appropriate knowledge in a short time seems difficult. Knowledge Recommender systems، Online Forums and Question Answering (QA) systems were created to facilitate finding suitable information. QA systems use knowledge repositories to retrieve brief responses to users’ queries. Expert Finding system، not only causes knowledge transition from responder to requester، but also it improves requester’s experience and thoughts about the subject. These systems use textual analysis، historical activities analysis، social relation analysis and combination of these approaches to find experts. In this paper، we used resume data of university professors to develop a new model which outperforms conventional methods by using Vector Space Model and Query Expansion Technique.