7 citations · 8 across the 4 of their papers we have counts for
4 papers
Cluster Language Model for Improved E-Commerce Retrieval and Ranking: Leveraging Query Similarity and Fine-Tuning for Personalized Results
Duleep Rathgamage Don, Ying Xie, Le Yu +2
This paper proposes a novel method to improve the accuracy of product search in e-commerce by utilizing a cluster language model. The method aims to address the limitations of the…
De-Biased Modelling of Search Click Behavior with Reinforcement Learning
Jianghong Zhou, Sayyed M. Zahiri, Simon Hughes +3
Users' clicks on Web search results are one of the key signals for evaluating and improving web search quality and have been widely used as part of current state-of-the-art Learnin…
APRF-Net: Attentive Pseudo-Relevance Feedback Network for Query Categorization
Ali Ahmadvand, Sayyed M. Zahiri, Simon Hughes +3
Query categorization is an essential part of query intent understanding in e-commerce search. A common query categorization task is to select the relevant fine-grained product cate…
Online Product Feature Recommendations with Interpretable Machine Learning
Mingming Guo, Nian Yan, Xiquan Cui +2
Product feature recommendations are critical for online customers to purchase the right products based on the right features. For a customer, selecting the product that has the bes…