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Context-aware Youtube recommender system

机译:上下文感知YouTube推荐系统

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摘要

Youtube is one of the most popular video sharing online resource that has millions of users around the world. The huge bulk of videos, which are growing at a high rate is posing problems for users to traverse through to relevant content. Users are facilitated with recommended videos that appeal to there interests. Following a hybrid recommendation approach, videos are recommended based on both collaborative recommendation and content-based recommendation. A limitation associated to this approach is that the videos recommended may not necessarily be appropriate to the current context that the user is in. Its very common for a single user to follow different interests depending of on the context they are in. A context-aware recommender system is proposed for Youtube that keeps track of multiple interests of a user and recommends videos based on their current context only. It serves a user better in finding relevant videos and has higher relevance to human judgment.
机译:YouTube是最受欢迎的视频共享在线资源之一,拥有全球数百万用户。巨大的批量视频,以高速增长而越来越大的视频是对用户遍历相关内容的问题。用户有助于提出吸引有利息的推荐视频。在混合推荐方法之后,基于协作建议和基于内容的建议建议视频。与这种方法相关的限制是推荐的视频可能不一定适合用户所在的当前上下文。对于单个用户来说,这是根据他们所在的上下文遵循不同的兴趣。一个上下文感知为YouTube提出了推荐系统,这些系统跟踪用户的多重兴趣,并仅推荐基于当前上下文的视频。它为用户提供更好地找到相关视频,并与人类判断具有更高的相关性。

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