汽车:情景感知推荐系统研讨会2022

G. Adomavicius, Konstantin Bauman, B. Mobasher, Francesco Ricci, Alexander Tuzhilin, Moshe Unger
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引用次数: 1

摘要

上下文信息已被广泛认为是社会科学和计算领域一个重要的建模维度。特别是,上下文在提高推荐结果和检索性能方面的作用已经得到认可。虽然大量的现有研究集中在上下文感知推荐系统(CARS)上,但许多有趣的问题仍未得到充分探索。CARS 2022研讨会提供了一个展示和讨论的场所:下一代CARS的重要特征;以及可能需要使用新型上下文信息并在组推荐和在线环境中处理其动态属性的应用程序领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CARS: Workshop on Context-Aware Recommender Systems 2022
Contextual information has been widely recognized as an important modeling dimension in social sciences and in computing. In particular, the role of context has been recognized in enhancing recommendation results and retrieval performance. While a substantial amount of existing research has focused on context-aware recommender systems (CARS), many interesting problems remain under-explored. The CARS 2022 workshop provides a venue for presenting and discussing: the important features of the next generation of CARS; and application domains that may require the use of novel types of contextual information and cope with their dynamic properties in group recommendations and in online environments.
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