Rahul Bhagat


Augmenting Training Data for Massive Semantic Matching Models in Low-Traffic E-commerce Stores
Ashutosh Joshi | Shankar Vishwanath | Choon Teo | Vaclav Petricek | Vishy Vishwanathan | Rahul Bhagat | Jonathan May
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track

Extreme multi-label classification (XMC) systems have been successfully applied in e-commerce (Shen et al., 2020; Dahiya et al., 2021) for retrieving products based on customer behavior. Such systems require large amounts of customer behavior data (e.g. queries, clicks, purchases) for training. However, behavioral data is limited in low-traffic e-commerce stores, impacting performance of these systems. In this paper, we present a technique that augments behavioral training data via query reformulation. We use the Aggregated Label eXtreme Multi-label Classification (AL-XMC) system (Shen et al., 2020) as an example semantic matching model and show via crowd-sourced human judgments that, when the training data is augmented through query reformulations, the quality of AL-XMC improves over a baseline that does not use query reformulation. We also show in online A/B tests that our method significantly improves business metrics for the AL-XMC model.


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Squibs: What Is a Paraphrase?
Rahul Bhagat | Eduard Hovy
Computational Linguistics, Volume 39, Issue 3 - September 2013


Large Scale Acquisition of Paraphrases for Learning Surface Patterns
Rahul Bhagat | Deepak Ravichandran
Proceedings of ACL-08: HLT

Weakly-Supervised Acquisition of Labeled Class Instances using Graph Random Walks
Partha Pratim Talukdar | Joseph Reisinger | Marius Paşca | Deepak Ravichandran | Rahul Bhagat | Fernando Pereira
Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing


LEDIR: An Unsupervised Algorithm for Learning Directionality of Inference Rules
Rahul Bhagat | Patrick Pantel | Eduard Hovy
Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)

ISP: Learning Inferential Selectional Preferences
Patrick Pantel | Rahul Bhagat | Bonaventura Coppola | Timothy Chklovski | Eduard Hovy
Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Proceedings of the Main Conference


Statistical Shallow Semantic Parsing despite Little Training Data
Rahul Bhagat | Anton Leuski | Eduard Hovy
Proceedings of the Ninth International Workshop on Parsing Technology