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All Journal Proceeding of the Electrical Engineering Computer Science and Informatics
Sam F. Chaerul Haviana
Universitas Islam Sultan Agung Semarang
Computer Science & IT Electrical & Electronics Engineering

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Obtaining Reference's Topic Congruity in Indonesian Publications using Machine Learning Approach Sam F. Chaerul Haviana; Imam Much Ibnu Subroto
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1971

Abstract

There are some criteria on how an article is categorized as a good article for publications. It could depend on some aspect like formatting and clarity, but mainly it depends on how the content of the article is constructed. The consistency of the topic that the article was written could show us how the authors construct the main idea in the article content. One indication that shows this consistency is congruity in the article’s topic and the topic of literature or reference cited in the document listed in the bibliography. This works attempting to automate the topic detection on the article’s references then obtain the congruity to the article title’s topic through metadata extraction and text classification. This is done by extracting metadata of an article file to obtain all possible reference title using GROBID than classify the topic using a supervised classification model. We found that some refinements in the whole approach should be considered in the next step of this work.
Co-Authors Imam Much Ibnu Subroto