第二届基于内容的推荐系统新趋势研讨会(CBRecSys 2015)

Toine Bogers, M. Koolen
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引用次数: 4

摘要

虽然基于内容的推荐已经成功地应用于许多不同的领域,但它还没有像协同过滤技术那样受到同等程度的关注。然而,在许多推荐领域和应用程序中,内容和元数据扮演着关键的角色,除了评级和隐式使用数据之外,还扮演着重要的角色。对于某些领域,例如电影,内容和使用数据之间的关系已经得到了彻底的研究,但是对于许多其他领域,例如书籍、新闻、科学文章和Web页面,我们仍然不知道这些数据源是否以及如何组合以提供最佳的推荐性能。CBRecSys 2015研讨会旨在通过为致力于基于内容的推荐的各个方面的论文提供一个专门的场所来解决这个问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Second Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2015)
While content-based recommendation has been applied successfully in many different domains, it has not seen the same level of attention as collaborative filtering techniques have. However, there are many recommendation domains and applications where content and metadata play a key role, either in addition to or instead of ratings and implicit usage data. For some domains, such as movies, the relationship between content and usage data has seen thorough investigation already, but for many other domains, such as books, news, scientific articles, and Web pages we still do not know if and how these data sources should be combined to provided the best recommendation performance. The CBRecSys 2015 workshop aims to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommendation.
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