Real Time Recommendation Utilizing Experts´ Experiences

The overload of information makes it too time consuming for common users to find what they really want in time. But it is easier for an expert to seek the related information he wants because of his rich search experiences and domain knowledge. Based on above idea and our previous works, we redesign our recommendation method, which can utilize experts´ experiences to recommend experts´ search histories for plenty of common users in real time. Furthermore, in order to support this method and solve expansibility problem of recommender system, we propose storage solution for experts´ search histories and design two related algorithms, then we take Nutch search engine as a basic platform to validate our method and algorithms. The experimental results show that our method is effective and the algorithms satisfy high-speed response.