IUI 2021 Tutorial on Conversational Recommendation Systems

Zuohui Fu, Yikun Xian, Yongfeng Zhang, Yi Zhang
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引用次数: 3

Abstract

Recent years have witnessed the emerging of conversational systems, including both physical devices and mobile-based applications. Both the research community and industry believe that conversational systems will have a major impact on human-computer interaction, and specifically, the CHI/IR/DM/RecSys communities have begun to explore Conversational Recommendation Systems. Conversational recommendation aims at finding or recommending the most relevant information (e.g., web pages, answers, movies, products) for users based on textual- or spoken-dialogs, through which users can communicate with the system more efficiently using natural language conversations. Due to users’ constant need to look for information to support both work and daily life, conversational recommendation system will be one of the key techniques towards an intelligent web. The tutorial focuses on the foundations and algorithms for conversational recommendation, as well as their applications in real-world systems such as search engine, e-commerce and social networks. The tutorial aims at introducing and communicating conversational recommendation methods to the community, as well as gathering researchers and practitioners interested in this research direction for discussions, idea communications, and research promotions.
IUI 2021会话推荐系统教程
近年来出现了会话系统,包括物理设备和基于移动的应用程序。研究界和工业界都认为会话系统将对人机交互产生重大影响,特别是CHI/IR/DM/RecSys社区已经开始探索会话推荐系统。会话式推荐旨在基于文本或口头对话为用户寻找或推荐最相关的信息(如网页、答案、电影、产品),用户可以通过自然语言对话更有效地与系统进行交流。由于用户在工作和日常生活中不断需要寻找信息,会话推荐系统将成为智能网络的关键技术之一。本教程侧重于会话推荐的基础和算法,以及它们在搜索引擎、电子商务和社交网络等现实系统中的应用。本教程旨在向社区介绍和传播会话推荐方法,并聚集对该研究方向感兴趣的研究人员和实践者进行讨论,思想交流和研究推广。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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