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首页> 外文期刊>American Journal of Applied Mathematics >Association Rule Mining for the Talents Introduction Strategy: A Case Study of Zhejiang University of Finance & Economics
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Association Rule Mining for the Talents Introduction Strategy: A Case Study of Zhejiang University of Finance & Economics

机译:关联规则挖掘的人才引进策略-以浙江财经大学为例

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In recent years, the issues of the talents introduction have attracted more and more researchers' and college administrators' attention. In the era of big data, data mining technology is widely used in various fields and has achieved remarkable results. The application of data mining technology in the introduction of university talents is in the ascendant. This paper uses the effective information of 245 teachers recruited by Zhejiang University of Finance & Economics since 2011 to explore and model the association rules. It preprocesses the raw information data by hierarchical clustering, and use Apriori algorithm to obtain a set of rules for the paper score and the situation of receiving the National Foundation of China (NFC) in 3 years. These rules will provide a constructive guiding significance for the introduction of talents in Zhejiang University of Finance & Economics.
机译:近年来,人才引进问题引起了越来越多研究人员和高校管理人员的关注。在大数据时代,数据挖掘技术已广泛应用于各个领域,并取得了显著成效。数据挖掘技术在大学人才引进中的应用方兴未艾。本文利用自2011年以来浙江财经大学聘用的245名教师的有效信息来探索和建模关联规则。它通过分层聚类对原始信息数据进行预处理,并使用Apriori算法获得一套针对论文得分和3年后获得中国国家基金会(NFC)状况的规则。这些规定将为浙江财经大学的人才引进提供建设性的指导意义。

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