From Social Network to Semantic Social Network in Recommender System

摘要: Due the success of emerging Web 2.0, and different social network sites such as Amazon movie lens, recommender systems are creating unprecedented opportunities to help people browsing web when looking for relevant information, making choices. Generally, these classified in three categories: content based, collaborative filtering, hybrid based recommendation systems. Usually, employ standard methods artificial neural networks, nearest neighbor, or Bayesian networks. However, approaches limited compared on applications, networks semantic web. In this paper, we propose a novel approach called that enhance analysis exploiting power analysis. Experiments real-world data from examine quality our method well performance algorithms.