Communications of the ACM - Special issue on computer graphics: state of the arts
Knowledge based approach to semantic composition of teams in an organization
Proceedings of the 2005 ACM symposium on Applied computing
Team recommendation in open innovation networks
Proceedings of the third ACM conference on Recommender systems
Location-based team recommendation in computer gaming scenarios
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Querying and Mining Uncertain Spatio-Temporal Data
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Teams are an important organizational unit and need to be composed appropriately. Whenever a high number of possible team members exists, the complexity of the composition task can not be effectively handled by humans. To support the composition in this scenario, team recommenders can be used. In this paper we discuss and formalize a flexible approach using a generic meta model for implementing various team composition strategies derived from a literature review. In order to demonstrate its use and its compatibility with a generic team recommendation approach, we then translate some of the theoretical team composition approaches found in the literature.