6 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,…
A Chain-of-Thought Approach to Semantic Query Categorization in e-Commerce Taxonomies
Jetlir Duraj, Ishita Khan, Kilian Merkelbach +1
Search in e-Commerce is powered at the core by a structured representation of the inventory, often formulated as a category taxonomy. An important capability in e-Commerce with hie…
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…
Extracting Important Tokens in E-Commerce Queries with a Tag Interaction-Aware Transformer Model
Md. Ahsanul Kabir, Mohammad Al Hasan, Aritra Mandal +4
The major task of any e-commerce search engine is to retrieve the most relevant inventory items, which best match the user intent reflected in a query. This task is non-trivial due…