Case Recommendation Based on Fuzzy Clustering in Personalization Web Services

摘要

Aiming at the problems of no strong real-time performance and poor scalability using traditional filtering recommendation technology, and a novel case recommended based on fuzzy clustering is proposed in this paper. Using case-based reasoning technology to personalized recommendation system, and the old case is clustered using fuzzy clustering algorithm, and a classification model is built, and the target case-the case base is converted to the target case-case class to reduce the most case retrieval space of the target case's the nearest neighbors. The experimental results indicate that this method can effectively improve the real-time performance, and it is used in E-commerce recommendation systems, and the degree of recommendation results universe of discourse is improved.