article · Scientific Programming · 2021
Multiclass Event Classification from Text
Daler Ali, Malik Muhammad Saad Missen, Mujtaba Husnain
Cited by 31Open access
Abstract
Social media has become one of the most popular sources of information. People communicate with each other and share their ideas, commenting on global issues and events in a multilingual environment. While social media has been popular for several years, recently, it has given an exponential rise in online data volumes because of the increasing popularity of local languages on the web. This allows researchers of the NLP community to exploit the richness of different languages while overcoming the challenges posed by these languages. Urdu is also one of the most used local languages being used on social media. In this paper, we presented the first-ever event detection approach for Urdu language text. Multiclass event classification is performed by popular deep learning (DL) models, i.e.,Convolution Neural Network (CNN), Recurrence Neural Network (RNN), and Deep Neural Network (DNN). The one-hot-encoding, word embedding, and term-frequency inverse document frequency- (TF-IDF-) based feature vectors are used to evaluate the Deep Learning(DL) models. The dataset that is used for experimental work consists of more than 0.15 million (103965) labeled sentences. DNN classifier has achieved a promising accuracy of 84% in extracting and classifying the events in the Urdu language script.
Cite this paper
Ali, D., Missen, M. M. S., & Husnain, M. (2021). Multiclass Event Classification from Text. Scientific Programming, 2021, 1–15. https://doi.org/10.1155/2021/6660651
Ali, Daler, et al. “Multiclass Event Classification from Text.” Scientific Programming, vol. 2021, 2021, pp. 1–15, https://doi.org/10.1155/2021/6660651.
Ali, Daler, Malik Muhammad Saad Missen, and Mujtaba Husnain. 2021. “Multiclass Event Classification from Text.” Scientific Programming 2021: 1–15. https://doi.org/10.1155/2021/6660651.
Ali, D., Missen, M.M.S. and Husnain, M. (2021) ‘Multiclass Event Classification from Text’, Scientific Programming, 2021, pp. 1–15. Available at: https://doi.org/10.1155/2021/6660651.
@article{ali2021multiclass,
title = {{Multiclass Event Classification from Text}},
author = {Ali, Daler and Missen, Malik Muhammad Saad and Husnain, Mujtaba},
journal = {Scientific Programming},
volume = {2021},
pages = {1--15},
year = {2021},
doi = {10.1155/2021/6660651}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.