Research on Trust Recommender Model based on experts´ social networks

Trust recommender systems can depend on users´ previous opinions and other trustworthy users´ opinions on items suggest to them items they will like. However, it is very important to discern and find trustworthy users´ opinions. In fact, it is easier for experts to find higher quality Web pages safely in search engines and trustworthy search histories are produced at the same time. Based on this observation, we firstly introduce a Trust Recommender Model (TRM) in this paper and it can recommend trustworthy Web pages to users through utilizing experts and their search histories based on experts´ social networks. Then, we propose an approach to identify right experts for a given queries and a fast traversing experts´ social network algorithm, which can be used to recommend trustworthy experts´ search histories in real time. In addition, in order to illuminate and validate proposed methods and algorithm, a Web pages recommender system is implemented through extending the open source search engine “Nutch”.