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Research and Development




Resources

Following resources are freely available for research purposes only. If you use these resources please cite relevant papers
• English Hindi Question Answering

- A Deep Neural Network Framework for English Hindi Question Answering
Paper    DataSet    Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
DEEPAK GUPTA, ASIF EKBAL, and PUSHPAK BHATTACHARYYA, A Deep Neural Network Framework for English Hindi Question Answering, In the ACM Trans. Asian Low-Resour. Lang. Inf. Process., Vol. 19, No. 2, Article 25. Publication date: November 2019.


• Question Generation and Neural Based Question Answering

- Uncovering Code-Mixed Challenges: A Framework for Linguistically Driven Question Generation and Neural Based Question Answering
Paper    DataSet    Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Deepak Gupta, Pabitra Lenka, Asif Ekbal, Pushpak Bhattacharyya, Uncovering Code-Mixed Challenges: A Framework for Linguistically Driven Question Generation and Neural Based Question Answering, In the Proceedings of the 22nd Conference on Computational Natural Language Learning.


• Semantic Question Matching

- Can Taxonomy Help? Improving Semantic Question Matching using Question Taxonomy
Paper    DataSet    Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Deepak Gupta, Rajkumar Pujari, Asif Ekbal, Pushpak Bhattacharyya, Anutosh Maitra, Tom Jain, Shubhashis Sengupta, Can Taxonomy Help? Improving Semantic Question Matching using Question Taxonomy, In the Proceedings of the 27th International Conference on Computational Linguistics.


• Multi-domain Multi-lingual Question-Answering

- MMQA: A Multi-domain Multi-lingual Question-Answering Framework for English and Hindi
Paper    DataSet    Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Deepak Gupta, Surabhi Kumari, Asif Ekbal, Pushpak Bhattacharyya, MMQA: A Multi-domain Multi-lingual Question-Answering Framework for English and Hindi, In the Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018).


• Cross-Lingual Natural Language Inference

- A Neural Framework for English-Hindi Cross-Lingual Natural Language Inference
Paper    DataSet    Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Tanik Saikh, Arkadipta De, Dibyanayan Bandyopadhyay, Baban Gain, and Asif Ekbal, A Neural Framework for English-Hindi Cross-Lingual Natural Language Inference, In the International Conference on Neural Information Processing (ICONIP) 2020, 18-22 November, 2020.


• Multi-modal Sarcasm, Sentiment and Emotion Analysis

-Sentiment and Emotion help Sarcasm? A Multi-task Learning Framework for Multi-Modal Sarcasm, Sentiment and Emotion Analysis
Paper    Download Link    Bibtex
By using the dataset you agree to use it for research purpose only and cite the below paper.
Dushyant Singh Chauhan, Dhanush S R, Asif Ekbal, Pushpak Bhattacharyya Sentiment and Emotion help Sarcasm? A Multi-task Learning Framework for Multi-Modal Sarcasm, Sentiment and Emotion Analysis, In the Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.


LREC 2020 Datasets


• Event Extraction

- A Platform for Event Extraction in Hindi
Paper    Download Link    Bibtex
By using the dataset you agree to use it for research purpose only and cite the below paper.
Sovan Kumar Sahoo, Saumajit Saha, Asif Ekbal, Pushpak Bhattacharyya A Platform for Event Extraction in Hindi, In the Proceedings of the 2020 Conference on Language Resources and Evaluation Conference (LREC 2020); Marseille, France, May 13-15, 2020.
• Emotion Annotated Suicide Notes

- CEASE, a Corpus of Emotion Annotated Suicide notes in English
Paper    Download Link    Bibtex
By using the dataset you agree to use it for research purpose only and cite the below paper.
Soumitra Ghosh, Asif Ekbal, Pushpak Bhattacharyya, CEASE, a Corpus of Emotion Annotated Suicide notes in English, In the Proceedings of the 2020 Conference on Language Resources and Evaluation Conference (LREC 2020); Marseille, France, May 13-15, 2020.
• Multi-domain Tweet Corpora for Sentiment Analysis

- Multi-domain Tweet Corpora for Sentiment Analysis: Resource Creation and Evaluation
Paper    Download Link    Bibtex
By using the dataset you agree to use it for research purpose only and cite the below paper.
Mamta, Asif Ekbal, Pushpak Bhattacharyya ,Shikha Srivastava, Alka Kumar, Tista Saha, Multi-domain Tweet Corpora for Sentiment Analysis: Resource Creation and Evaluation, In the Proceedings of the 2020 Conference on Language Resources and Evaluation Conference (LREC 2020); Marseille, France, May 13-15, 2020.
• Dataset for Machine Reading Comprehension on Scholarly Articles

- ScholarlyRead: A New Dataset for Scientific Article Reading Comprehension
Paper    Download Link   
By using the dataset you agree to use it for research purpose only and cite the below paper.
Tanik Saikh, Asif Ekbal and Pushpak Bhattacharyya, ScholarlyRead: A New Dataset for Scientific Article Reading Comprehension, In the Proceedings of the 2020 Conference on Language Resources and Evaluation Conference (LREC 2020); Marseille, France, May 13-15, 2020.


• Multi-modal Sentiment and Emotion Analysis

- Context-aware Interactive Attention for Multi-modal Sentiment and Emotion Analysis
Paper    GitHub Code Link   
By using the code you agree to use it for research purpose only and cite the below paper.
Dushyant Singh Chauhan, Md Shad Akhtar, Asif Ekbal and Pushpak Bhattacharyya, Context-aware Interactive Attention for Multi-modal Sentiment and Emotion Analysis, In the Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP 2019); Hong Kong, China, November 3–7, 2019.


• Medical Sentiment Analysis

- Medical sentiment analysis using social media: towards building a patient assisted system Dataset
Paper    DataSet    Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Shweta Yadav, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya, Medical Sentiment Analysis using Social Media: Towards building a PatientAssisted System, In the Proceedings of the 11th International Conference on Language Resource and Evaluation (LREC 2018); Miyazaki-Japan, 7-12th May, 2018.


• TAP-DLND 1.0 - English

- TAP-DLND 1.0 : A Corpus For Document Level Novelty Detection
Fill Form    Bibtex    Paper    ReadMe    License    Download
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Tirthankar Ghosal, Amitra Salam, Swati Tiwari, Asif Ekbal, Pushpak Bhattacharyya; TAP-DLND 1.0 : A Corpus For Document Level Novelty Detection; in the Proceedings of the 11th International Conference on Language Resource and Evaluation (LREC 2018); Miyazaki-Japan, 7-12th May, 2018.



• Tweet Temporal Orientation

- Fine-grained Temporal Orientation
Paper    Email the authors for accessing Dataset    Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Sabyasachi Kamila, Mohammed Hasanuzzaman, Asif Ekbal, Pushpak Bhattacharyya and Andy Way; Fine-grained Temporal Orientation and Its Relationship with Psycho-demographic Correlates; Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL:HLT 2018), Volume 1 (Long Papers); New Orleans, USA; 1st-6th June, 2018.


• Bilingual Word Embeddings

- Bilingual Word Embeddings - English/Hindi & English/French
Paper    English-Hindi Bilingual WE    English-French Bilingual WE    Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Md Shad Akhtar, Palaash Sawant, Sukanta Sen, Asif Ekbal, Pushpak Bhattacharyya; Solving Data Sparsity for Aspect based Sentiment Analysis using Cross-linguality and Multi-linguality; to appear in the Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL:HLT 2018); New Orleans, USA; 1st-6th May, 2018.


• Review Sentiment Datasets - Hindi

- Review sentiment dataset for aspect term extraction and sentiment classification
Paper    Download    Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Md Shad Akhtar, Asif Ekbal, Pushpak Bhattacharyya; Aspect Based Sentiment Analysis in Hindi: Resource Creation and Evaluation; In proceedings of the 10th International Conference on Language Resource and Evaluation (LREC 2016); 23-28; Portoroz, Slovenia; 2016.
- Review sentiment dataset for aspect category detection and sentiment classification
Paper    Download    Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Md Shad Akhtar, Asif Ekbal, Pushpak Bhattacharyya; Aspect Based Sentiment Analysis: Category Detection and Sentiment Classification for Hindi; In proceedings of the 17th International Conference on Intelligent Text Processing and Computational Linguistics (CICLING 2016); Konya, Turkey; 2016.
- Review sentiment dataset for sentence level sentiment classification
Paper    Download    Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Md Shad Akhtar, Ayush Kumar, Asif Ekbal, Pushpak Bhattacharyya; A Hybrid Deep Learning Architecture for Sentiment Analysis; In proceedings of the 26th International Conference on Computational Linguistics (COLING 2016); 482-493; Osaka, Japan; 2016.
- Movie review sentiment dataset for sentence level sentiment classification
Paper    Download    Bibtex
By downloading you agree to use the datasets for research purpose only and cite the below paper.
Md Shad Akhtar, Ayush Kumar, Asif Ekbal, Pushpak Bhattacharyya; A Hybrid Deep Learning Architecture for Sentiment Analysis; In proceedings of the 26th International Conference on Computational Linguistics (COLING 2016); 482-493; Osaka, Japan; 2016.