Analysis of the quality of academic papers by the words in abstracts

Tetsuya Nakatoh, Kenta Nagatani, Toshiro Minami, Sachio Hirokawa, Takeshi Nanri, Miho Funamori

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The investigation of related research is very important for research activities. However, it is not easy to choose an appropriate and important academic paper from among the huge number of possible papers. The researcher searches by combining keywords and then selects an paper to be checked because it uses an index that can be evaluated. The citation count is commonly used as this index, but information about recently published papers cannot be obtained. This research attempted to identify good papers using only the words included in the abstract. We constructed a classifier by machine learning and evaluated it using cross validation. As a result, it was found that a certain degree of discrimination is possible.

Original languageEnglish
Title of host publicationHuman Interface and the Management of Information
Subtitle of host publicationSupporting Learning, Decision-Making and Collaboration - 19th International Conference, HCI International 2017, Proceedings
EditorsSakae Yamamoto
PublisherSpringer Verlag
Pages434-443
Number of pages10
ISBN (Print)9783319585239
DOIs
Publication statusPublished - Jan 1 2017
EventThematic track on Human Interface and the Management of Information, held as part of the 19th International Conference on Human–Computer Interaction, HCI International 2017 - Vancouver, Canada
Duration: Jul 9 2017Jul 14 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10274 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherThematic track on Human Interface and the Management of Information, held as part of the 19th International Conference on Human–Computer Interaction, HCI International 2017
CountryCanada
CityVancouver
Period7/9/177/14/17

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Nakatoh, T., Nagatani, K., Minami, T., Hirokawa, S., Nanri, T., & Funamori, M. (2017). Analysis of the quality of academic papers by the words in abstracts. In S. Yamamoto (Ed.), Human Interface and the Management of Information: Supporting Learning, Decision-Making and Collaboration - 19th International Conference, HCI International 2017, Proceedings (pp. 434-443). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10274 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-58524-6_34