A literature research on machine learning techniques used for training annotated corpus

Rumaisa, Fitrah and Basiron, Halizah and Saaya, Zurina and Khamis, Noorli (2019) A literature research on machine learning techniques used for training annotated corpus. International Journal of Recent Technology and Engineering, 8 (2S8). pp. 1331-1337. ISSN 2277-3878

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Abstract

The development of research in the annotation area is growing. Researchers perform annotation task using various forms of datasets such as text, sound, images, and videos. Various algorithms are used to perform tasks. The purpose of this survey is to find out algorithms that are often used by researchers to perform annotation tasks, especially on text data. The literature surveys thirteen research papers on text annotation from the last 5 years. The results of this review indicate that SVM is the algorithm used for all three annotation methods: manual, automatic and semi-automatic annotation, with a significant accuracy above 80%. The result of this survey will be referred by the authors as the basis for subsequent research that will be conducted, especially in the semi-automatic annotation method.

Item Type:	Article
Uncontrolled Keywords:	Algorithm, Annotation, Semi-automatic, Text survey
Divisions:	Faculty of Information and Communication Technology
Depositing User:	Sabariah Ismail
Date Deposited:	07 Dec 2020 10:32
Last Modified:	12 Jul 2023 11:19
URI:	http://eprints.utem.edu.my/id/eprint/24480
Statistic Details:	View Download Statistic

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