The dynamics of collective sorting robot-like ants and ant-like robots
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
A Formal Model for User Preference
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Using of Clustering and Ant-Colony Algorithms CWSP-PAM-ANT in Network Planning
ICDT '06 Proceedings of the international conference on Digital Telecommunications
Cluster Analysis Based on Artificial Immune System and Ant Algorithm
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 03
A gaussian-fuzzy content feature recognition system for digital media asset objects
ICADL'04 Proceedings of the 7th international Conference on Digital Libraries: international collaboration and cross-fertilization
A search ant and labor ant algorithm for clustering data
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hi-index | 0.00 |
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.