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E-commerce search framework boosts new item sales by 5.3%

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new retrieval framework called GrowthGR to address the "Matthew effect" in e-commerce search, where popular items are over-represented. This framework aims to balance immediate sales with the long-term growth potential of new items. GrowthGR was successfully deployed on Taobao, resulting in a 5.3% increase in new item Gross Merchandise Volume (GMV) and a 0.3% gain in overall search GMV. AI

IMPACT Improves e-commerce search by promoting new items and increasing overall sales.

RANK_REASON The cluster describes a research paper proposing and evaluating a new framework for e-commerce search. [lever_c_demoted from research: ic=1 ai=0.7]

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

E-commerce search framework boosts new item sales by 5.3%

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The cluster describes a research paper proposing and evaluating a new framework for e-commerce search. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    Towards Sustainable Growth: A Multi-Value-Aware Retrieval Framework for E-Commerce Search

    New item growth is critical for maintaining a healthy ecosystem in large-scale e-commerce platforms. However, existing systems tend to prioritize presenting users with already popular items, a phenomenon often referred to as the "Matthew effect". In the context of search retrieva…

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