An ACO-Based User Community Preference Clustering System for Customized Content Service in Broadband New Media Platforms

With the rapidly increasing implementation and popularity of broadband new media platforms in recent years, the effective personalized content service model has become a key issue in the establishment and development of New Media. In this paper we propose a user preference clustering framework for the customization of content service in broadband new media platforms, i.e. IPTV, digital TV, video portals and mobile video communities. By introducing the ant colony optimization (ACO) algorithm as the basic strategy of multi-agent clustering method in the system, the work in this paper has resulted in a technical approach for the establishment of the personalized service of large-scale broadband new media environments.