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Systems and methods for personalized generalized content recommendations

机译:用于个性化广义内容推荐的系统和方法

摘要

Users receive content recommendations from a personalized, generalized recommendation service that aggregates and selects content of high personal relevance to each individual user from a large pool of both personal and public content. The received content is filtered and the content determined to be relevant is cached. When a user request for content is received, the cached content is rescored and the content determined to be most relevant based on satisfaction of a relevance threshold is selected and forwarded to the user. Feedback methodologies are also implemented so that a user's actions are taken into consideration in real time and can affect subsequent recommendations to the user.
机译:用户从个性化的,通用的推荐服务中接收内容推荐,该服务会从大量的个人和公共内容中汇总并选择与每个个人用户具有高度个人相关性的内容。过滤接收到的内容,并缓存确定为相关的内容。当接收到用户对内容的请求时,对缓存的内容进行重新评分,并且基于对相关性阈值的满足确定为最相关的内容被选择并转发给用户。还实施了反馈方法,以便实时考虑用户的动作,并且可以影响对用户的后续建议。

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