cs.AI updates on arXiv.org 10月15日 13:13
电商搜索中品牌实体链接问题研究
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本文针对电商搜索中的品牌实体链接问题,提出了一种两阶段方法,结合命名实体识别与匹配,并设计了一种新型的端到端解决方案,使用极端多分类分类。通过离线基准测试和在线A/B测试验证了方法的有效性。

arXiv:2502.01555v2 Announce Type: replace-cross Abstract: In this work, we address the brand entity linking problem for e-commerce search queries. The entity linking task is done by either i)a two-stage process consisting of entity mention detection followed by entity disambiguation or ii) an end-to-end linking approaches that directly fetch the target entity given the input text. The task presents unique challenges: queries are extremely short (averaging 2.4 words), lack natural language structure, and must handle a massive space of unique brands. We present a two-stage approach combining named-entity recognition with matching, and a novel end-to-end solution using extreme multi-class classification. We validate our solutions by both offline benchmarks and the impact of online A/B test.

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品牌实体链接 电商搜索 命名实体识别 端到端学习 多分类分类
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