9 citations · 23 across the 14 of their papers we have counts for
13 papers · 1 filter
Overview of the TREC 2025 Product Search and Recommendation Track
Dean E. Alvarez, Surya Kallumadi, Daniel Campos +4
In the past few years, consumers have moved the bulk of their product exploration and purchasing efforts online seeking speed, convenience, and price comparison with ease unimagina…
Bridging Personalization and Control in Scientific Personalized Search
Sheshera Mysore, Garima Dhanania, Kishor Patil +3
Personalized search is a problem where models benefit from learning user preferences from per-user historical interaction data. The inferred preferences enable personalized ranking…
Overview of the TREC 2023 Product Product Search Track
Daniel Campos, Surya Kallumadi, Corby Rosset +2
This is the first year of the TREC Product search track. The focus this year was the creation of a reusable collection and evaluation of the impact of the use of metadata and multi…
A Personalized Dense Retrieval Framework for Unified Information Access
Hansi Zeng, Surya Kallumadi, Zaid Alibadi +2
Developing a universal model that can efficiently and effectively respond to a wide range of information access requests -- from retrieval to recommendation to question answering -…
A Boring-yet-effective Approach for the Product Ranking Task of the Amazon KDD Cup 2022
Vitor Jeronymo, Guilherme Rosa, Surya Kallumadi +2
In this work we describe our submission to the product ranking task of the Amazon KDD Cup 2022. We rely on a receipt that showed to be effective in previous competitions: we focus…
Diversifying Multi-aspect Search Results Using Simpson's Diversity Index
Jianghong Zhou, Eugene Agichtein, Surya Kallumadi
In search and recommendation, diversifying the multi-aspect search results could help with reducing redundancy, and promoting results that might not be shown otherwise. Many previo…
De-Biased Modelling of Search Click Behavior with Reinforcement Learning
Jianghong Zhou, Sayyed M. Zahiri, Simon Hughes +3
Users' clicks on Web search results are one of the key signals for evaluating and improving web search quality and have been widely used as part of current state-of-the-art Learnin…
DeepCAT: Deep Category Representation for Query Understanding in E-commerce Search
Ali Ahmadvand, Surya Kallumadi, Faizan Javed +1
Mapping a search query to a set of relevant categories in the product taxonomy is a significant challenge in e-commerce search for two reasons: 1) Training data exhibits severe cla…
APRF-Net: Attentive Pseudo-Relevance Feedback Network for Query Categorization
Ali Ahmadvand, Sayyed M. Zahiri, Simon Hughes +3
Query categorization is an essential part of query intent understanding in e-commerce search. A common query categorization task is to select the relevant fine-grained product cate…
Semantic Product Search for Matching Structured Product Catalogs in E-Commerce
Jason Ingyu Choi, Surya Kallumadi, Bhaskar Mitra +2
Retrieving all semantically relevant products from the product catalog is an important problem in E-commerce. Compared to web documents, product catalogs are more structured and sp…
JointMap: Joint Query Intent Understanding For Modeling Intent Hierarchies in E-commerce Search
Ali Ahmadvand, Surya Kallumadi, Faizan Javed +1
An accurate understanding of a user's query intent can help improve the performance of downstream tasks such as query scoping and ranking. In the e-commerce domain, recent work in…
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…
A Line in the Sand: Recommendation or Ad-hoc Retrieval?
Surya Kallumadi, Bhaskar Mitra, Tereza Iofciu
The popular approaches to recommendation and ad-hoc retrieval tasks are largely distinct in the literature. In this work, we argue that many recommendation problems can also be cas…