An Interactive And Intelligent Mechanism For Establishing Knowledge Structure Of On-line Talents

Online innovation outsourcing is the behavior by which corporations utilize human resources outside the organization to complete a certain task. Within this commercial mode, corporations are able to exert the talents of R&D researchers without establishing employment relationship with them. This mode can help cut down the costs of R&D for corporations and serves as a desirable way to improve their competitiveness. Besides, on-line outsourcing provides more opportunities for the talents in society, which will help lower fictional unemployment.As the communication infrastructure and Internet technology develop rapidly, the material conditions for realizing online outsourcing have matured. However, how to spot proper R&D researchers for a particular task and how to find proper innovation task for the talents remain the bottleneck of the expansion of online outsourcing mode. In order to realize this match, we need to describe the talent structure of the online R&D researchers in the first place. This paper, based on relation data model and relative algorithm, designs an automatic mechanism to build the knowledge structure of online R&D researchers, providing foundations for establishing competency model and designing ability-matching algorithm.Firstly, this paper proposes a multi-layer mechanism to store knowledge structure of online R&D researchers. This mechanism includes three layers: major-course standard database, college-major-course, user-major-course, and can keep data redundancy at the lowest level and realize efficient storage to meet the requirements of processing large amount of information of R&D researchers in online environment.Secondly, this paper proposes a method to calculate the similarity of courses and cluster courses. This algorithm makes computer able to identify the semantics of knowledge structure of R&D researchers, and provides foundations for establishing standard major-course database and designing machine learning algorithm to establish college-major-course database.Finally, we proposed an automatic method to establish college-major-course. This method is able to partially solve the problem of incompleteness and discredit of the online information provided by the R&D researchers. We developed a prototype system to implement all the algorithms and methods proposed above.The storage mechanism and algorithm proposed in this paper can be generally used to describe knowledge structure of online R&D researchers, which provides guidance for intermediary platform of online outsourcing to build database for talents.