Abstract—Academic papers submitted to a conference are
assessed by reviewers and judged if they deserve to be presented
at the conference. The accepted papers are often classified into
full papers, short papers, and other types, according mainly to
the reviewers’ assessment. The major aim of the study
presented in this paper is to find tips which are effective for a
paper to be improved so that a paper supposed to be classified
as a short paper becomes a full paper. In this study, we
investigate a scenario for finding the differences between full
and short papers on the usage of words/terms. Then, we extract
words which are characteristic for either full or short papers
through an experimental study. In order to find these words, we
introduce a couple of indexes of a word. The results inspire that
we can obtain practical tips in this approach by refining this
method.
Index Terms—Academic material, data mining, feature
finding.
T. Minami was with Kyushu Institute of Information Sciences (KIIS),
6-3-1 Saifu, Dazaifu, Fukuoka 818-0117 Japan (e-mail:
minamitoshiro@gmail.com, ohura@kiis.ac.jp).
Y. Ohura is with Kyushu Institute of Information Sciences (KIIS), 6-3-1
Saifu, Dazaifu, Fukuoka 818-0117 Japan (e-mail: ohura@kiis.ac.jp).
Cite: Toshiro Minami and Yoko Ohura, "How Different Are Full and Short Papers in Word-Usage?," International Journal of Machine Learning and Computing vol. 10, no. 4, pp. 582-587, 2020.
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).