A new strategy for developing scientific community model based on scientific article publication

Achmad Maududie, Slamin, Agus Subekti, Daniel Siahaan, Prihandoko, Hotniar Siringoringo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The study was a literature review to develop a new strategy to clustering data. This study is part of our ongoing main project to develop scientific community model based on scientific article publication. The concept of this strategy is utilizing scientific article metadata elements that has been published electronically to map scientists community respect to the topics that are developing. This paper introduces TermRank approach that is adopted from PageRank to determine the strength value of a node and implements clustering technique to limit the number of computation in the topic modeling. Based on preliminary results, it is shown that in the stage of article data extraction, it turns out that it must be readjusted by adding the number of process to solve the problems on inconsistency inputting metadata elements, the use of two languages in abstract, and non-standard references format.

Original languageEnglish
Title of host publication7th International Conference on Information Science and Technology, ICIST 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages259-262
Number of pages4
ISBN (Electronic)9781509054015
DOIs
Publication statusPublished - 11 May 2017
Event7th International Conference on Information Science and Technology, ICIST 2017 - Da Nang, Viet Nam
Duration: 16 Apr 201719 Apr 2017

Publication series

Name7th International Conference on Information Science and Technology, ICIST 2017 - Proceedings

Conference

Conference7th International Conference on Information Science and Technology, ICIST 2017
Country/TerritoryViet Nam
CityDa Nang
Period16/04/1719/04/17

Keywords

  • Clustering
  • Scientific Article Publication
  • Scientific Community Model
  • TermRank

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