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Collaborative-filtering content model for recommending items

机译:推荐内容的协同过滤内容模型

摘要

Methods and apparatus for a recommendation system based on collaborative filtering is provided. Explicit and implicit ratings of items by network users are used to create a contextual model. The explicit ratings comprise different rating types regarding different item attributes. The implicit ratings comprise different rating types derived from different user events and may include recency, intensity, or frequency ratings. The contextual model may be optimized for a specific objective function, such as click-through-rate or conversion rate. In other embodiments, item information is used to produce a content model where item information for an item is encoded as metadata into a document that represents the item. The contextual or content model is used to recommend one or more items to a current user. The basic unit of the recommendation system may be an item set of two or more items or a particular sequence of two or more items.
机译:提供了基于协作过滤的推荐系统的方法和装置。网络用户对项目的显式和隐式评级用于创建上下文模型。显式评分包括有关不同项目属性的不同评分类型。隐式等级包括从不同用户事件派生的不同等级类型,并且可以包括新近度,强度或频率等级。可以针对特定目标功能(例如点击率或转化率)优化上下文模型。在其他实施例中,项目信息用于产生内容模型,其中用于项目的项目信息被作为元数据编码到表示该项目的文档中。上下文或内容模型用于向当前用户推荐一个或多个项目。推荐系统的基本单元可以是两个或多个项目的项目集合,或者是两个或多个项目的特定序列。

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