@inproceedings{debina-saharia-2021-delab,
title = "{DEL}ab@{IIITSM} at {ICON}-2021 Shared Task: Identification of Aggression and Biasness Using Decision Tree",
author = "Debina, Maibam and
Saharia, Navanath",
editor = "Kumar, Ritesh and
Singh, Siddharth and
Nandi, Enakshi and
Ratan, Shyam and
Devi, Laishram Niranjana and
Lahiri, Bornini and
Bansal, Akanksha and
Bhagat, Akash and
Dawer, Yogesh",
booktitle = "Proceedings of the 18th International Conference on Natural Language Processing: Shared Task on Multilingual Gender Biased and Communal Language Identification",
month = dec,
year = "2021",
address = "NIT Silchar",
publisher = "NLP Association of India (NLPAI)",
url = "https://aclanthology.org/2021.icon-multigen.5",
pages = "35--40",
abstract = "This paper presents our system description on participation in ICON-2021 Shared Task sub-task 1 on multilingual gender-biased and communal language identification as team name: DELab@IIITSM. We have participated in two language-specific Meitei, Hindi, and one multi-lingualMeitei, Hindi, and Bangla with English code-mixed languages identification task. Our method includes well design pre-processing phase based on the dataset, the frequency-based feature extraction technique TF-IDF which creates the feature vector for each instance using(Decision Tree). We obtained weights are 0.629, 0.625, and 0.632 as the overall micro F1 score for the Hindi, Meitei, and multilingual datasets.",
}
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<abstract>This paper presents our system description on participation in ICON-2021 Shared Task sub-task 1 on multilingual gender-biased and communal language identification as team name: DELab@IIITSM. We have participated in two language-specific Meitei, Hindi, and one multi-lingualMeitei, Hindi, and Bangla with English code-mixed languages identification task. Our method includes well design pre-processing phase based on the dataset, the frequency-based feature extraction technique TF-IDF which creates the feature vector for each instance using(Decision Tree). We obtained weights are 0.629, 0.625, and 0.632 as the overall micro F1 score for the Hindi, Meitei, and multilingual datasets.</abstract>
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%0 Conference Proceedings
%T DELab@IIITSM at ICON-2021 Shared Task: Identification of Aggression and Biasness Using Decision Tree
%A Debina, Maibam
%A Saharia, Navanath
%Y Kumar, Ritesh
%Y Singh, Siddharth
%Y Nandi, Enakshi
%Y Ratan, Shyam
%Y Devi, Laishram Niranjana
%Y Lahiri, Bornini
%Y Bansal, Akanksha
%Y Bhagat, Akash
%Y Dawer, Yogesh
%S Proceedings of the 18th International Conference on Natural Language Processing: Shared Task on Multilingual Gender Biased and Communal Language Identification
%D 2021
%8 December
%I NLP Association of India (NLPAI)
%C NIT Silchar
%F debina-saharia-2021-delab
%X This paper presents our system description on participation in ICON-2021 Shared Task sub-task 1 on multilingual gender-biased and communal language identification as team name: DELab@IIITSM. We have participated in two language-specific Meitei, Hindi, and one multi-lingualMeitei, Hindi, and Bangla with English code-mixed languages identification task. Our method includes well design pre-processing phase based on the dataset, the frequency-based feature extraction technique TF-IDF which creates the feature vector for each instance using(Decision Tree). We obtained weights are 0.629, 0.625, and 0.632 as the overall micro F1 score for the Hindi, Meitei, and multilingual datasets.
%U https://aclanthology.org/2021.icon-multigen.5
%P 35-40
Markdown (Informal)
[DELab@IIITSM at ICON-2021 Shared Task: Identification of Aggression and Biasness Using Decision Tree](https://aclanthology.org/2021.icon-multigen.5) (Debina & Saharia, ICON 2021)
ACL