12 citations · 28 across the 6 of their papers we have counts for
8 papers
INSPIRE: Intent-aware Neural Sponsored Product Retrieval for E-commerce
Shasvat Desai, Hong Yao, Utkarsh Porwal +1
Walmart holds the largest share of the U.S. ecommerce grocery market, where food and beverage categories generate some of the highest search traffic and, consequently, drive a subs…
Unified Supervision for Walmart's Sponsored Search Retrieval via Joint Semantic Relevance and Behavioral Engagement Modeling
Shasvat Desai, Md Omar Faruk Rokon, Jhalak Nilesh Acharya +4
Modern search systems rely on a fast first stage retriever to fetch relevant items from a massive catalog of items. Deployed search systems often use user engagement signals to sup…
Report on the SIGIR 2019 Workshop on eCommerce (ECOM19)
Jon Degenhardt, Surya Kallumadi, Utkarsh Porwal +1
The SIGIR 2019 Workshop on eCommerce (ECOM19), was a full day workshop that took place on Thursday, July 25, 2019 in Paris, France. The purpose of the workshop was to serve as a pl…
Learning Image Information for eCommerce Queries
Utkarsh Porwal
Computing similarity between a query and a document is fundamental in any information retrieval system. In search engines, computing query-document similarity is an essential step…
Position Bias Estimation for Unbiased Learning-to-Rank in eCommerce Search
Grigor Aslanyan, Utkarsh Porwal
The Unbiased Learning-to-Rank framework has been recently proposed as a general approach to systematically remove biases, such as position bias, from learning-to-rank models. The m…
Credit Card Fraud Detection in e-Commerce: An Outlier Detection Approach
Utkarsh Porwal, Smruthi Mukund
Often the challenge associated with tasks like fraud and spam detection is the lack of all likely patterns needed to train suitable supervised learning models. This problem accentu…
Outlier Detection by Consistent Data Selection Method
Utkarsh Porwal, Smruthi Mukund
Often the challenge associated with tasks like fraud and spam detection[1] is the lack of all likely patterns needed to train suitable supervised learning models. In order to overc…
Spelling Correction as a Foreign Language
Yingbo Zhou, Utkarsh Porwal, Roberto Konow
In this paper, we reformulated the spell correction problem as a machine translation task under the encoder-decoder framework. This reformulation enabled us to use a single model f…