Papers by Aniket Chakrabarti

2 papers
Distantly Supervised Aspect Clustering And Naming For E-Commerce Reviews (2022.naacl-industry)

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Challenge: Product aspect extraction from reviews is a critical task for e-commerce services . scale of reviews makes human review at ecommerce scale infeasible.
Approach: They propose automated methods for extracting aspect phrases from reviews . they train transformer based sentence embeddings that are aware of unique e-commerce language characteristics .
Outcome: The proposed method improves the Silhouette Score by 64% compared to the state-of-the-art model . human review at e-commerce scale is infeasible due to the scale of the reviews .
Distantly Supervised Transformers For E-Commerce Product QA (2021.naacl-main)

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Challenge: e-commerce services often provide an instant QA system on product pages . however, user queries and CQA pairs differ significantly in language characteristics .
Approach: They propose a transformer-based instant question answering system on product pages . for each user query, relevant community question answer (CQA) pairs are retrieved . their framework is able to scale to large e-commerce QA traffic .
Outcome: The proposed model outperforms syntactic and semantic baselines on user queries and training with CQA pairs.

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