Information Acquisition and Analysis Technology of Personalized Recommendation System Based on Case-Based Reasoning for Internet of Things

摘要

In the paper, we discuss the theories of the information acquisition and analysis and the information quality of the case-based reasoning (CBR) personalized recommendation system. We also take a deep study of the key techniques of acquiring and analyzing information quality. With research results of this paper, combined with the content-based recommendation technology and recommendation results of collaborative filtering, a CBR-based personalized combinatorial recommendation algorithm is designed.