Search Results for author:
Found 3 papers, 0 papers with code
Semantic Equivalence of e-Commerce Queries
Behavioral similarity leverages historical search behavior to generate vector representations of query intent.
ORDSIM: Ordinal Regression for E-Commerce Query Similarity Prediction
ORDSIM exploits variable-width buckets to model ordinal loss, which penalizes errors in high-level similarity harshly, and thus enable the regression model to obtain better prediction results for high similarity values.
Personalized Ranking in eCommerce Search
We address the problem of personalization in the context of eCommerce search.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
