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Found 5 papers, 0 papers with code
De-Biased Modelling of Search Click Behavior with Reinforcement Learning
Our experiments demonstrate the effectiveness of the DRLC model in learning to reduce bias in click logs, leading to improved modeling performance and showing the potential for using DRLC for improving Web search quality.
Online Product Feature Recommendations with Interpretable Machine Learning
For a customer, selecting the product that has the best trade-off between price and functionality is a time-consuming step in an online shopping experience, and customers can be overwhelmed by the available choices.
BIG-bench Machine Learning
Interpretable Machine Learning
+2
Deep Learning-based Online Alternative Product Recommendations at Scale
In this paper, we use both textual product information (e. g. product titles and descriptions) and customer behavior data to recommend alternative products.
Interpretable Methods for Identifying Product Variants
For e-commerce companies with large product selections, the organization and grouping of products in meaningful ways is important for creating great customer shopping experiences and cultivating an authoritative brand image.
Entity Type Recognition using an Ensemble of Distributional Semantic Models to Enhance Query Understanding
The data set contains entities extracted from millions of job seekers/recruiters search queries, job postings, and resume documents.
