3 papers
cs.IR2025
LESER: Learning to Expand via Search Engine-feedback Reinforcement in e-Commerce
Yipeng Zhang, Bowen Liu, Xiaoshuang Zhang +3
User queries in e-commerce search are often vague, short, and underspecified, making it difficult for retrieval systems to match them accurately against structured product catalogs…
cs.LG2025
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…
cs.IR2024
A Survey on E-Commerce Learning to Rank
Md. Ahsanul Kabir, Mohammad Al Hasan, Aritra Mandal +2
In e-commerce, ranking the search results based on users' preference is the most important task. Commercial e-commerce platforms, such as, Amazon, Alibaba, eBay, Walmart, etc. perf…