Multichannel LSTM-CNN for Telugu Technical Domain Identification
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Abstract (arXiv)
With the instantaneous growth of text information, retrieving domain-oriented information from the text data has a broad range of applications in Information Retrieval and Natural language Processing. Thematic keywords give a compressed representation of the text. Usually, Domain Identification plays a significant role in Machine Translation, Text Summarization, Question Answering, Information Extraction, and Sentiment Analysis. In this paper, we proposed the Multichannel LSTM-CNN methodology for Technical Domain Identification for Telugu. This architecture was used and evaluated in the context of the ICON shared task TechDOfication 2020 (task h), and our system got 69.9% of the F1 score on the test dataset and 90.01% on the validation set.
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References · 4
- 2016Enriching Word Vectors with Subword Informationcited by 1,583
- 2015Show, Attend and Tell: Neural Image Caption Generation with Visual Attentioncited by 1,423
- 2018Learning Word Vectors for 157 Languagescited by 280
- 2020Multichannel CNN with Attention for Text Classificationcited by 5
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