Third Workshop on Personalization and Recommendations in Search (PaRiS)

被引：0

作者：

Lamkhede, Sudarshan ^{[1
]}

Zamani, Hamed ^{[2
]}

Bhattacharya, Moumita ^{[1
]}

Wang, Hongning ^{[3
]}

机构：

[1] Netflix Res, Los Gatos, CA 95032 USA

[2] Univ Massachusetts Amherst, Amherst, MA USA

[3] Univ Virginia, Dept Comp Sci, Charlottesville, VA USA

来源：

PROCEEDINGS OF THE 47TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH AND DEVELOPMENT IN INFORMATION RETRIEVAL, SIGIR 2024 | 2024年

关键词：

Search; Personalization; Recommendations; Generative AI; LLM;

D O I：

10.1145/3626772.3657983

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With proliferation of personal computing devices and large number of logged-in experiences, search has evolved to a stage with many different product scenarios where personalization plays a crucial role for relevance quality and user satisfaction. The purpose of this workshop is have a forum where latest research and advancements specifically on Personalization and Recommendations in Search (PaRiS) can be discussed in conjunction with SIGIR 2024. This will be the third instance of this workshop. We held two very successful instances of this workshop at the WebConf 2023 [5] and WSDM 2022. This year we will especially focus on applications of LLMs and Generative AI to enable personalization and recommendations [1] in the context of search, for example, conversational assistants, while continuing to use this workshop for discussing other advances and applications in the context of personalized search and recommendations in the context of search.

引用

页码：3065 / 3069

页数：5

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