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"…
Iterating Toward Better Search: A Two-Agent Simulation Framework for Evaluating Agentic Search Architectures in E-Commerce
Jetlir Duraj, Jayanth Yetukuri, Shuang Zhou +4
We present a modular two-agent simulation framework for evaluating conversational shopping assistant architectures. An independent buyer agent, configured with personas, missions,…
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…
Intent-Aware Neural Query Reformulation for Behavior-Aligned Product Search
Jayanth Yetukuri, Ishita Khan
Understanding and modeling buyer intent is a foundational challenge in optimizing search query reformulation within the dynamic landscape of e-commerce search systems. This work in…