5 papers
IntentTune: Using user demand and personalization to resolve "unknown" query intents for e-commerce search
Rachith Aiyappa, Ishita Khan, Chester Palen-Michel +4
Understanding user intent is fundamental to delivering relevant search results in e-commerce. However, substantial fraction of real-world queries are under-specified (e.g., "watch"…
Improving Search Suggestions for Alphanumeric Queries
Samarth Agrawal, Jayanth Yetukuri, Diptesh Kanojia +2
Alphanumeric identifiers such as manufacturer part numbers (MPNs), SKUs, and model codes are ubiquitous in e-commerce catalogs and search. These identifiers are sparse, non linguis…
AI Guided Accelerator For Search Experience
Jayanth Yetukuri, Mehran Elyasi, Samarth Agrawal +4
Effective query reformulation is pivotal in narrowing the gap between a user's exploratory search behavior and the identification of relevant products in e-commerce environments. W…
NEAR: A Nested Embedding Approach to Efficient Product Retrieval and Ranking
Shenbin Qian, Diptesh Kanojia, Samarth Agrawal +4
E-commerce information retrieval (IR) systems struggle to simultaneously achieve high accuracy in interpreting complex user queries and maintain efficient processing of vast produc…
Centrality-aware Product Retrieval and Ranking
Hadeel Saadany, Swapnil Bhosale, Samarth Agrawal +3
This paper addresses the challenge of improving user experience on e-commerce platforms by enhancing product ranking relevant to users' search queries. Ambiguity and complexity of…