KLASIFIKASI HOMONIM-SINONIM PADA BIBLIOGRAFI DIGITAL LIBRARY DENGAN MENGGUNAKAN METODE MACHINE LEARNING

PUTRA, VARINDO OCKTA KENEDDI and Firdaus, Firdaus (2020) KLASIFIKASI HOMONIM-SINONIM PADA BIBLIOGRAFI DIGITAL LIBRARY DENGAN MENGGUNAKAN METODE MACHINE LEARNING. Undergraduate thesis, Sriwijaya University.

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Abstract

The process of finding an author's name for a publication becomes more complicated because of the case of Homonyms and Synonyms. Although many researchers in the world have classified Homonym data or Synonym data from a Digital Library Bibliography dataset, in this study the classification is done at once for Homonym data, Synonym data, Homonym-Synonym data, and Non Homonym-Synonym data. The classification in this study was carried out using three classifiers, namely Support Vector Machine (SVM), Decision Tree, and Deep Neural Network (DNN). With the DBLP dataset and the three Classifiers, the classification is done in twenty one trials (model / scenario). From all experiments, each classifier has a best model / scenario that is judged by the good performance value generated. Among the sixteen models / scenario scenarios conducted using DNN, there are two best models / scenarios that produce the highest accuracy values. These two models / scenarios are the best models / scenarios for all experiments of all Classifiers.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Digital Library, Bibliographic Data, Author Name Disambiguation, Homonym, Synonym, Deep Neural Network, Support Vector Machine, Decision Tree.
Subjects: T Technology > T Technology (General) > T1-995 Technology (General)
T Technology > T Technology (General) > T60-60.8 Work measurement. Methods engineering
Divisions: 09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User: Users 5370 not found.
Date Deposited: 10 Jul 2020 04:52
Last Modified: 10 Jul 2020 04:52
URI: http://repository.unsri.ac.id/id/eprint/31162

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