a novel recommender system fusing the opinions from experts and ordinary people
In this paper, we propose a novel recommendation algorithm fusing the opinions from experts and ordinary people. Instead of regarding one's judgement capability as his/her expertise, we present a new definition which measures the amount of the recommendable items one know in a certain area. When computing the expertise, we consider both the average value and the accumulative value, and introduce a free parameter ? to tune between these two values. To evaluate the proposed algorithm, simulations are run on the Moviepilot dataset, and the results demonstrate that our algorithm outperforms the conventional collaborative filtering algorithm.
recommender systems collaborative filtering experts finding