Papers by Rashmi Patange
Weakly supervised hierarchical multi-task classification of customer questions (2023.acl-industry)
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Jitenkumar Rana, Promod Yenigalla, Chetan Aggarwal, Sandeep Sricharan Mukku, Manan Soni, Rashmi Patange
| Challenge: | Identifying granular and actionable topics from customer questions helps improve the overall customer experience. |
| Approach: | They propose a weakly supervised Hierarchical Multi-task Classification Framework to identify granular topics from customer questions . a clustering based taxonomy creation and data labeling module is used to create taxonomies and labelled data with minimal supervision. |
| Outcome: | The proposed model achieves 13% better accuracy over single-task classification frameworks . it can adapt to constantly evolving taxonomy without need of re-training . |
InsightNet : Structured Insight Mining from Customer Feedback (2023.emnlp-industry)
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Sandeep Sricharan Mukku, Manan Soni, Chetan Aggarwal, Jitenkumar Rana, Promod Yenigalla, Rashmi Patange, Shyam Mohan
| Challenge: | Existing methods for extracting structured insights from reviews suffer from drawbacks . lack of structure, non-standard aspect names, lack of abundant training data limit their effectiveness and applicability. |
| Approach: | They propose a semi-supervised multi-level taxonomy from raw customer reviews and a semantic similarity heuristic approach to generate labelled data. |
| Outcome: | The proposed approach outperforms existing methods in structure, hierarchy and completeness. |