AUTHOR NAMES DISAMBIGUATION DALAM KLASIFIKASI AUTHOR MATCHING DENGAN MENGGUNAKAN METODE MACHINE LEARNING PADA PENDEKATAN ANOMALY DETECTION

YAMANI A, ZAQQI and Nurmaini, Siti and Rini, Dian Palupi (2020) AUTHOR NAMES DISAMBIGUATION DALAM KLASIFIKASI AUTHOR MATCHING DENGAN MENGGUNAKAN METODE MACHINE LEARNING PADA PENDEKATAN ANOMALY DETECTION. Master thesis, Sriwijaya University.

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Abstract

Author Name Disambiguation (AND) is a problem that reduces the quality of information in publication. Quality of service is strongly influenced in the problem of ambiguity of author names in citations and considered to be the most difficult issues in digital library from researchers and has an impact on the information of authors, organizations and other matters presented as part of the publication. Therefore, anomaly detection approach is proposed to solve this problem. The method proposed is using the isolationForest algorithm and local Outlier Factor (LOF) which produces an accuracy score 95%.

Item Type:	Thesis (Master)
Uncontrolled Keywords:	Author Name Disambiguation (AND), deteksi anomali
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55101-Informatics (S2)
Depositing User:	Zaki Yamani
Date Deposited:	01 Oct 2020 12:03
Last Modified:	01 Oct 2020 12:03
URI:	http://repository.unsri.ac.id/id/eprint/36036

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