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Semantic Analysis Techniques using Twitter Datasets on Big Data: Comparative Analysis Study

Belal Abdullah Hezam Murshed1,∗, Hasib Daowd Esmail Al-ariki2,†, Suresha Mallappa3,‡

1,3 University of Mysore, Department of Studies in Computer Science, Mysore, Karnataka, India
2 Sana’a Community College,Department of Computer Networks Engineering and Technologies, Sana’a, Yemen
† hasibalariki@gmail.com
‡ sureshasuvi@gmail.com

* Corresponding Author: Belal Abdullah Hezam Murshed, email

Computer Systems Science and Engineering 2020, 35(6), 495-512. https://doi.org/10.32604/csse.2020.35.495

Abstract

This paper conducts a comprehensive review of various word and sentence semantic similarity techniques proposed in the literature. Corpus-based, Knowledge-based, and Feature-based are categorized under word semantic similarity techniques. String and set-based, Word Order-based Similarity, POSbased, Syntactic dependency-based are categorized as sentence semantic similarity techniques. Using these techniques, we propose a model for computing the overall accuracy of the twitter dataset. The proposed model has been tested on the following four measures: Atish’s measure, Li’s measure, Mihalcea’s measure with path similarity, and Mihalcea’s measure with Wu and Palmer’s (WuP) similarity. Finally, we evaluate the proposed method on three real-world twitter datasets. The proposed model based on Atish’s measure seems to offer good results in all datasets when compared with the proposed model based on other sentence similarity measures.

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APA Style
Murshed, B.A.H., Al-ariki, H.D.E., Mallappa, S. (2020). Semantic analysis techniques using twitter datasets on big data: comparative analysis study. Computer Systems Science and Engineering, 35(6), 495-512. https://doi.org/10.32604/csse.2020.35.495
Vancouver Style
Murshed BAH, Al-ariki HDE, Mallappa S. Semantic analysis techniques using twitter datasets on big data: comparative analysis study. Comput Syst Sci Eng. 2020;35(6):495-512 https://doi.org/10.32604/csse.2020.35.495
IEEE Style
B.A.H. Murshed, H.D.E. Al-ariki, and S. Mallappa, “Semantic Analysis Techniques using Twitter Datasets on Big Data: Comparative Analysis Study,” Comput. Syst. Sci. Eng., vol. 35, no. 6, pp. 495-512, 2020. https://doi.org/10.32604/csse.2020.35.495

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cc Copyright © 2020 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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