KEYPHRASE EXTRACTION MENGGUNAKAN PRETRAINED LANGUAGE MODEL ROBERTA DAN POSITION AWARE GRAPH

KHADAFI, M. BINTANG and Yusliani, Novi and Rodiah, Desty (2024) KEYPHRASE EXTRACTION MENGGUNAKAN PRETRAINED LANGUAGE MODEL ROBERTA DAN POSITION AWARE GRAPH. Undergraduate thesis, Sriwijaya University.

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Abstract

Searching for the desired scientific journal from the many published journals is currently a challenge for researchers because it takes a lot of time. Therefore, the use of keyphrases or keywords that represent the content of scientific journals is needed as a solution to save search time. The keyphrase extraction process is carried out to obtain relevant keyphrases. One of the keyphrase extraction methods is Position Aware Graph combined with a pretrained language model called RoBERTa to represent language vectors. This research aims to create a keyphrase extraction system using Pretrained Language Model RoBERTa and Position Aware Graph. In the test, 100 datasets containing title and abstract data of scientific journals were used. The test results show that the best configuration is keyphrase extraction with the selection of 10 selected keyphrases with an average f1-score value of 0.1434.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Jurnal Ilmiah, Keyphrase, Keyphrase Extraction, Position Aware Graph, Pretrained Language Model, RoBERTa
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	M. Bintang Khadafi
Date Deposited:	22 Mar 2024 02:27
Last Modified:	22 Mar 2024 02:27
URI:	http://repository.unsri.ac.id/id/eprint/142121

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