To Distinguish Full and Short Papers using Commonness of Words

Proceedings of the 13th International Conference on Computer Modeling and Simulation Pub Date : 2021-06-25 DOI:10.1145/3474963.3475846

Toshiro Minami, Y. Ohura

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Abstract

Our eventual goal regarding this study is to support students with developing paper-writing skill. In order to achieve this goal, we have been trying to find characteristic features of good papers through analyzing educational and other kinds of data. We take conference papers as target data and suppose full/regular papers are good because they are chosen as reviewers evaluate them more valuable to be presented in the conference than other papers. In our series of study, we have been surveying the differences of full and short papers. In this paper, we aim to investigate further differences of them by taking different analysis method. We have been using the numbers of occurrences of each word in full/short papers as the data for analysis. In this paper we use the numbers of full/short papers that contain the word instead of the total numbers of occurrences of words. We define a new index of a word which shows how likely it is used in full or short papers. We discuss its effectiveness by applying it to an experiment of distinguishing full and short papers.

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用词汇的共性来区分论文的长短

本研究的最终目标是帮助学生提高论文写作技能。为了实现这一目标，我们一直试图通过分析教育和其他类型的数据来发现优秀论文的特征。我们将会议论文作为目标数据，并假设完整/常规论文是好的，因为审稿人认为它们比其他论文更有价值，更值得在会议上发表。在我们的系列研究中，我们一直在研究长论文和短论文的区别。本文将采用不同的分析方法，进一步探讨两者之间的差异。我们一直使用论文中每个单词的出现次数作为分析数据。在本文中，我们使用包含单词的全文/短文的数量，而不是单词的总出现次数。我们定义了一个单词的新索引，它显示了该单词在全文或短文中使用的可能性。将该方法应用于论文全文和短文的区分实验，讨论了其有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 13th International Conference on Computer Modeling and Simulation

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