Abstract
Modern communication technologies, in particular social network services and mobiles Internet applications, have generated a tremendous hype enabling new forms of human interaction patterns. Millions of users voluntarily give away their preference profiles and want to share common interests in groups. Thus, the proper and efficient management of group preferences becomes a challenging area. Since any approach towards its solution should be scalable to even very large user groups, we propose a database-centered framework in this paper. We extend a well-known constructor-driven approach for modeling preferences as strict partial orders towards modeling
and optimization capabilities for dynamic group formation. Since the quality of group formations can be judged by semantic aspects like e.g. group homogeneity, group optimization techniques must be capable to properly take this aspect into consideration. In more detail we describe how to model the quality of group formations depending on individual group member preferences. Then we propose several optimization heuristics for subgroup formation, based on laws of preference algebra and also on statistical knowledge. In summary we are confident that the preliminary results presented here can be extended towards intuitive, robust and scalable algorithms for the dynamic management of even very large user groups with sophisticated preference profiles.
Authors
Florian Wenzel, Werner Kießling
Publication
Proceedings of the 5th Multidisciplinary Workshop on Advances in Preference Handling in conjunction with ECAI 2010, Aug. 16th, Lisbon, Portugal, 2010