Application of Big Data, Blockchain, and Internet of Things for Education Informatization. First EAI International Conference, BigIoT-EDU 2021, Virtual Event, August 1–3, 2021, Proceedings, Part II

Research Article

Research on Evaluation Mechanism of Innovation and Entrepreneurship Team Management Based on Data Mining Classification

  • @INPROCEEDINGS{10.1007/978-3-030-87903-7_34,
        author={Shuang Qiu},
        title={Research on Evaluation Mechanism of Innovation and Entrepreneurship Team Management Based on Data Mining Classification},
        proceedings={Application of Big Data, Blockchain, and Internet of Things for Education Informatization. First EAI International Conference, BigIoT-EDU 2021, Virtual Event, August 1--3, 2021, Proceedings, Part II},
        proceedings_a={BIGIOT-EDU PT2},
        year={2021},
        month={10},
        keywords={Data mining Evaluation index Performance evaluation Quantitative performance K-means clustering Decision tree algorithm},
        doi={10.1007/978-3-030-87903-7_34}
    }
    
  • Shuang Qiu
    Year: 2021
    Research on Evaluation Mechanism of Innovation and Entrepreneurship Team Management Based on Data Mining Classification
    BIGIOT-EDU PT2
    Springer
    DOI: 10.1007/978-3-030-87903-7_34
Shuang Qiu1
  • 1: Hubei University of Medicine

Abstract

In order to improve the quantitative performance appraisal mechanism in the existing innovation and Entrepreneurship Talent Management System, a research scheme based on data mining technology is proposed. The combination of decision tree algorithm and cluster analysis is applied to the quantitative performance appraisal system, so as to explore the relationship between the appraisal results and various factors. Kmeans clustering algorithm is used to evaluate and analyze the team members, which is roughly divided into four levels in the form of classification rules. According to the evaluation level and the core attributes of entrepreneurial team, the detailed final individual quantitative assessment score table is generated by using the decision tree algorithm. Taking the actual data of an entrepreneurial team as the sample to test, analyze and verify, the test results show that the proposed scheme has better accuracy, and provides strong decision support for talent team management.