第一个关于用户粘性优化的研讨会

Liangjie Hong, Shuang-Hong Yang
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引用次数: 1

摘要

在线用户参与优化是许多互联网业务的关键。有几个研究领域与在线用户参与优化的概念相关,包括机器学习、数据挖掘、信息检索、推荐系统、在线A/B(桶)测试和心理学。在过去,这方面的研究工作是在不同的社区和会议上进行的,产生了潜在的不连贯和重复的结果。此外,研究人员和实践者有时只接触到主题的一个特定方面,这可能是不完整的,对于整个画面来说是次优的。在这里,我们组织了关于在线用户参与优化主题的第一次研讨会,明确地将该主题作为一个整体,并将研究人员和从业者聚集在一起,以促进该领域的发展。我们邀请了两位业界领先的研究人员就在线机器学习和在线实验进行主题演讲。此外,还邀请了来自业界和学术界研究人员的几场演讲,涵盖了内容个性化、在线实验平台和推荐系统等主题。此外,六篇新颖的论文将被作为短篇论文纳入研讨会,以便在研讨会上讨论和分享新的成果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The first workshop on user engagement optimization
Online user engagement optimization is key to many Internet business. Several research areas are related to the concept of online user engagement optimization, including machine learning, data mining, information retrieval, recommender systems, online A/B (bucket) testing and psychology. In the past, research efforts in this direction are pursued in separate communities and conferences, yielding potential disconnected and repeated results. In addition, researchers and practitioners are sometimes only exposed to a specific aspect of the topic, which might be incomplete and suboptimal to the whole picture. Here, we organize the first workshop on the topic of online user engagement optimization, explicitly targeting the topic as a whole and bring researchers and practitioners together to foster the field. We invite two leading researchers from industry to give keynote talks about online machine learning and online experimentations. In addition, several invited talks from industry and academic researchers have covered the topics of content personalization, online experimental platforms and recommender systems. Also, six novel submissions are included as short papers in the workshop such that new results are discussed and shared among the workshop.
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