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Found 6 papers, 0 papers with code
Enhanced E-Commerce Attribute Extraction: Innovating with Decorative Relation Correction and LLAMA 2.0-Based Annotation
The rapid proliferation of e-commerce platforms accentuates the need for advanced search and retrieval systems to foster a superior user experience.
Leveraging Large Language Models for Enhanced Product Descriptions in eCommerce
In the dynamic field of eCommerce, the quality and comprehensiveness of product descriptions are pivotal for enhancing search visibility and customer engagement.
A Deep Reinforcement Learning Approach for Interactive Search with Sentence-level Feedback
Interactive search can provide a better experience by incorporating interaction feedback from the users.
RLIRank: Learning to Rank with Reinforcement Learning for Dynamic Search
To support this dynamic ranking paradigm effectively, search result ranking must incorporate both the user feedback received, and the information displayed so far.
Diversifying Multi-aspect Search Results Using Simpson's Diversity Index
In search and recommendation, diversifying the multi-aspect search results could help with reducing redundancy, and promoting results that might not be shown otherwise.
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.
