利用高校中期规划对高校进行自动评价与特征词分析

Kahori Ogashiwa, Eiichi Takata, Tetsuyake Oishi, M. Mori, S. Hirokawa
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引用次数: 0

摘要

日本国立大学必须根据逻辑模型制定中期计划。然而,由于不知道如何描述逻辑模型的五个观点(目的、输入、活动、输出和结果),大学仍然在苦苦挣扎。本文将机器学习应用于三期中期计划文本,根据逻辑模型进行分类,并调查其在识别各大学方面的表现。此外,对各高校的特色词汇进行了分析,揭示了各高校面临的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Estimation and Feature Word Analysis of Universities Using University Medium-term Plans
Japanese national universities are required to draw up medium-term plans based on logic models. However, universities continue to struggle due to not knowing how to describe the five viewpoints (purpose, input, activity, output and outcome) of the logic model. In this paper, machine learning was applied to the text of third-phase medium-term plans, categorized according to the logic model, and an investigation was made into its performance in identifying each university. In addition, the feature words of the universities were analyzed, revealing the issues facing each of them.
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