Alapan Kuila
2020
A Graph Convolution Network-based System for Technical Domain Identification
Alapan Kuila
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Ayan Das
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Sudeshna Sarkar
Proceedings of the 17th International Conference on Natural Language Processing (ICON): TechDOfication 2020 Shared Task
This paper presents the IITKGP contribution at the Technical DOmain Identification (TechDOfication) shared task at ICON 2020. In the preprocessing stage, we applied part-of-speech (PoS) taggers and dependency parsers to tag the data. We trained a graph convolution neural network (GCNN) based system that uses the tokens along with their PoS and dependency relations as features to identify the domain of a given document. We participated in the subtasks for coarse-grained domain classification in the English (Subtask 1a), Bengali (Subtask 1b) and Hindi language (Subtask 1d), and, the subtask for fine-grained domain classification task within Computer Science domain in English language (Subtask 2a).
2016
JU-USAAR: A Domain Adaptive MT System
Koushik Pahari
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Alapan Kuila
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Santanu Pal
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Sudip Kumar Naskar
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Sivaji Bandyopadhyay
|
Josef van Genabith
Proceedings of the First Conference on Machine Translation: Volume 2, Shared Task Papers
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Co-authors
- Koushik Pahari 1
- Santanu Pal 1
- Sudip Kumar Naskar 1
- Sivaji Bandyopadhyay 1
- Josef van Genabith 1
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