达尔文和歌利亚:一个带有自动算法选择的白标签推荐系统即服务

J. Beel, Alan Griffin, Conor O'Shea
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引用次数: 5

摘要

推荐即服务(RaaS)简化了中小型企业向其客户提供产品推荐的过程。然而,当前的RaaS存在“一刀切”的概念,即它们对所有中小企业应用相同的推荐算法。我们介绍了Darwin & Goliath,这是一个RaaS,具有多个推荐框架(Apache Lucene, TensorFlow,…),并自动识别每个SME的理想算法。Darwin & Goliath进一步提供了按实例算法选择和白标功能,允许中小企业以自己的品牌提供RaaS。自2018年11月以来,Darwin & Goliath已经提供了超过100万条推荐,CTR = 0.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Darwin & Goliath: a white-label recommender-system as-a-service with automated algorithm-selection
Recommendations-as-a-Service (RaaS) ease the process for small and medium-sized enterprises (SMEs) to offer product recommendations to their customers. Current RaaS, however, suffer from a one-size-fits-all concept, i.e. they apply the same recommendation algorithm for all SMEs. We introduce Darwin & Goliath, a RaaS that features multiple recommendation frameworks (Apache Lucene, TensorFlow, ...), and identifies the ideal algorithm for each SME automatically. Darwin & Goliath further offers per-instance algorithm selection and a white label feature that allows SMEs to offer a RaaS under their own brand. Since November 2018, Darwin & Goliath has delivered more than 1m recommendations with a CTR = 0.5%.
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