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New DCEO framework optimizes e-commerce search for long-term user value

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new framework called DCEO (Direct Causal Effect Optimization) to improve long-term user value modeling in e-commerce search. This data-driven approach aims to create item-level proxy scores that better align with ultimate user objectives, such as cumulative purchases or gross merchandise value (GMV). DCEO utilizes an actor-critic framework to directly optimize the causal effect, moving beyond traditional manually tuned fusion schemes. Deployed in a large-scale industrial e-commerce search system, DCEO demonstrated a 0.36% improvement in GMV over a conventional proxy in a 41-day online A/B test. AI

IMPACT This research could lead to more personalized and effective e-commerce search experiences by better aligning search results with long-term user value.

RANK_REASON Academic paper detailing a new optimization framework for e-commerce search. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.IR (Information Retrieval) →

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

New DCEO framework optimizes e-commerce search for long-term user value

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Academic paper detailing a new optimization framework for e-commerce search. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Haihong Tang ·

    DCEO: Direct Causal Effect Optimization for Long-Term User Value Modeling in E-commerce Search

    Industrial e-commerce search systems ultimately aim to optimize the user-level long-term objective, such as n-day cumulative purchases or gross merchandise value (GMV) per user. However, such objectives are defined at the user level, whereas search ranking is based on item-level …

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