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Project Teaming: Knowledge-intensive Design For Composing Team Members

机译：项目团队：组成团队成员的知识密集型设计

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摘要

Enterprises frequently use project teams to perform various tasks. In a human-centered, highly collaborative environment, the importance of teamwork exceeds that of individual skill. Appropriate team composition is crucial to the success of ad-hoc teamwork, yet optimizing team composition is challenging. This study utilizes knowledge-intensive approaches to build project teaming models into ontologies. Furthermore, it helps develop a set of logic rules for identifying semantic relationships between individuals. By following a knowledge-base creation process, the factual data of project, workers, and teaming factors can be inserted into ontologies. Based on knowledge inference, reliable knowledge bases are established for selecting project team members in runtime. A case study is presented to demonstrate the effectiveness of the proposed design. Experimental lessons demonstrate that combining rules with ontological knowledge bases not only serves team composition needs, but also achieves knowledge base durability and system reliability.
机译：企业经常使用项目团队来执行各种任务。在以人为中心，高度协作的环境中，团队合作的重要性超出了个人技能的重要性。适当的团队组成对于临时团队合作的成功至关重要，但是优化团队组成是一项挑战。这项研究利用知识密集型方法将项目团队模型构建到本体中。此外，它有助于开发一组逻辑规则以识别个人之间的语义关系。通过遵循知识库创建过程，可以将项目，工作人员和团队因素的事实数据插入到本体中。基于知识推断，建立了可靠的知识库，以便在运行时选择项目团队成员。案例研究表明了所提出设计的有效性。实验课程表明，将规则与本体知识库相结合不仅可以满足团队组成的需求，而且还可以提高知识库的持久性和系统可靠性。

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