Part of #A recommender system based on trust and semantics in collaborative systemsusing a new measure of association# :
Publishing year : 2014
Conference : First International Conference on Knowledge, Information and Software Engineering
Number of pages : 6
Abstract: One of the most popular techniques used in recommending systems is collaborating filtering. In this technique it is usual that Pearson's correlation is used to find the similarity between users. It is a known fact that Pearson's correlation is not suitable for measuring the strength of nonlinearrelations. Since Spearman's correlation is in fact Pearson's correlation is applied to ranks and does not work well in non-monotonous relationships, and since measures like Kendal'stau do not work well in small samples, we introduce a new measure of association to be used in collaborative systems which we Must call alpha. Our investigations show that it leads to a better MAE. We also propose a method by combining Alpha and trust propagation and add anew algorithm to semantic similarity for confronting the problems with cold start and it leads to better coverage.