BJUT at TREC 2014 Contextual Suggestion Track: Hybrid Recommendation Based on Open-web Information.

摘要

In this paper we describe our efforts for TREC contextual suggestion task. Our goal of this year is to evaluate the effectiveness of: (1) Preference crawling method that as far as possible to obtain more candidate spots' information from open-web to model the users' interest profiles; (2) Automatic summarization method that leverages the information from multiple resources to generate the description for each candidate scenic spots (3) Hybrid recommendation method that combing a variety of factors to construct a system of hybrid recommendation system. Finally, we conduct extensive experiments to evaluate the proposed framework on TREC 2014 Contextual Suggestion data set, and, as would be expected, the results demonstrate its generality and superior performance.