Papers by Swapnil Hingmire
R-VGAE: Relational-variational Graph Autoencoder for Unsupervised Prerequisite Chain Learning (2020.coling-main)
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| Challenge: | Concept prerequisite chain learning is an unsupervised task with no access to labeled concept pairs during training. |
| Approach: | They propose a model that uses deep learning representations to predict concept relations . they frame concept prerequisite chain learning as an unsupervised task with no labeled concept pairs . |
| Outcome: | The proposed model outperforms semi-supervised methods in terms of accuracy and F1 score. |
Extraction of Message Sequence Charts from Software Use-Case Descriptions (N19-2)
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Girish Palshikar, Nitin Ramrakhiyani, Sangameshwar Patil, Sachin Pawar, Swapnil Hingmire, Vasudeva Varma, Pushpak Bhattacharyya
| Challenge: | Software Requirement Specification documents provide natural language descriptions of the core functional requirements as a set of use-cases. |
| Approach: | They propose a linguistic knowledge-based approach to extract software requirements from use-cases using a textual representation of the core functional requirements. |
| Outcome: | The proposed method performs better than existing techniques and improves performance. |
Identification of Alias Links among Participants in Narratives (P18-2)
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Sangameshwar Patil, Sachin Pawar, Swapnil Hingmire, Girish Palshikar, Vasudeva Varma, Pushpak Bhattacharyya
| Challenge: | Identifying distinct and independent participants in a narrative is crucial for many NLP applications. |
| Approach: | They propose an approach based on linguistic knowledge for identification of aliases mentioned using proper nouns, pronouns or noun phrases with common noun headword. |
| Outcome: | The proposed approach performs better than the state-of-the-art approach on four diverse history narratives of varying complexity. |