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The Data Mining Technology Application in University's Scientific Research Management

Guo Bu-ming

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Abstract

University's information system has stored every rich aspect information, such as teaching, scientific research and management. The data is rich in content and broad in range. This paper applies the association rule Data Mining into the university's science and technology statistics relevance data, judge by mining purpose and data characteristic, design the mining system. Mining the data about teaching and scientific research, with the purpose of finding out the potential rules in teaching and scientific research. It will offer some help to the teaching activity and scientific research in the following year.

About this research paper

What this paper is about

University's information system has stored every rich aspect information, such as teaching, scientific research and management. The data is rich in content and broad in range. This paper applies the association rule Data Mining into the university's science and technology statistics relevance data, judge by mining purpose and data characteristic, design the mining system. Mining the data about teaching and scientific research, with the purpose of finding out the potential rules in teaching and scientific research. It will offer some help to the teaching activity and scientific research in the following year.

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Available abstract

University's information system has stored every rich aspect information, such as teaching, scientific research and management. The data is rich in content and broad in range. This paper applies the association rule Data Mining into the university's science and technology statistics relevance data, judge by mining purpose and data characteristic, design the mining system. Mining the data about teaching and scientific research, with the purpose of finding out the potential rules in teaching and scientific research. It will offer some help to the teaching activity and scientific research in the following year.

Key concepts: Relevance (law), Data science, Computer science, Association rule learning, Range (aeronautics), Data mining, Engineering, Aerospace engineering

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