A Study of Context Dependencies in Multi-page Product Search
Author:
Affiliation:
1. University of Massachusetts Amherst, Amherst, MA, USA
2. Search Labs, Amazon, Palo Alto, CA, USA
Funder
National Science Foundation
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3357384.3358095
Reference18 articles.
1. Learning a Hierarchical Embedding Model for Personalized Product Search
2. A probabilistic mixture model for mining and analyzing product search log
3. Multi-modal Preference Modeling for Product Search
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2. ROSE: Robust Caches for Amazon Product Search;Companion Proceedings of the Web Conference 2022;2022-04-25
3. Deep Learning Based Sentiment Aware Ranking for E-commerce Product Search;Advanced Intelligent Systems for Sustainable Development (AI2SD’2020);2022
4. Model-agnostic vs. Model-intrinsic Interpretability for Explainable Product Search;Proceedings of the 30th ACM International Conference on Information & Knowledge Management;2021-10-26
5. Deep Neural Network and Boosting Based Hybrid Quality Ranking for e-Commerce Product Search;Big Data and Cognitive Computing;2021-08-13
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