Construction and Analysis of IPTV User Profile Based on Multimedia Design

This study proposes a multimedia content classification algorithm based on massive IPTV themes, which extracts program themes through spectral clustering analysis of the correlation between frequent itemsets and user viewing behavior. The algorithm classifies the massive IPTV data into topics by considering factors such as user viewing behavior, live channel viewing characteristics, interactive on-demand viewing characteristics, and packaging operations that contribute to classification accuracy. Experimental results show that the algorithm’s accuracy is higher than that of traditional vector space-based methods, and it has good practicality and feasibility. By proposing a topic classification algorithm based on massive IPTV themes, this study achieves topic classification of massive IPTV data and provides users with more accurate program recommendations and personalized services, filling some knowledge gaps that previous articles were unable to solve. Our research provides a new idea and method for processing massive IPTV data and has some reference value for the future development of IPTV.