A literature research on machine learning techniques used for training annotated corpus
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 resear...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Blue Eyes Intelligence Engineering and Sciences Publication
2019
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| Online Access: | http://eprints.utem.edu.my/id/eprint/24480/2/ARTICLE-FITRAH-IJRTE02.PDF http://eprints.utem.edu.my/id/eprint/24480/ https://www.ijrte.org/wp-content/uploads/papers/v8i2S8/B10630882S819.pdf |
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| Summary: | 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. |
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