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1.发明授权Method and apparatus for efficiently recommending items using automated collaborative filtering and feature-guided automated collaborative filtering 失效使用自动协同过滤和特征引导的自动协同过滤来有效地推荐项目的方法和装置
公开(公告)号：US6092049A
公开(公告)日：2000-07-18
申请号：US818533
申请日：1997-03-14
CPC分类号： G06F17/30867 , G06F17/30699 , G06Q30/02 , G06Q30/0201 , G06Q30/0203 , G06Q30/06 , H04N21/252
摘要： A method for recommending items to users using automated collaborative filtering stores profiles of users relating ratings to items in memory. Profiles of items may also be stored in memory, the item profiles associating users with the rating given to the item by that user or inferred for the user by the system The user profiles include additional information relating to the user or associated with the rating given to an item by the user. Item profiles are retrieved to determine which users have rated a particular item. Profiles of those users are accessed and the ratings are used to calculate similarity factors with respect to other users. The similarity factors, sometimes in connection with confidence factors, are used to select a set of neighboring users. The neighboring users are weighted based on their respective similarity factors, and a rating for an item contained in the domain is predicted. In one embodiment, items in the domain have features. In this embodiment, the values for features can be clustered, and the similarity factors incorporate assigned feature weights and feature value cluster weights. In some embodiments, item concepts are used to enhance recommendation accuracy.
摘要翻译： 使用自动协同过滤向用户推荐项目的方法存储用户将评级与存储器中的项目相关联的简档。 项目的配置文件也可以存储在存储器中，项目简档将用户与由该用户给予的项目的评级相关联或由系统推断给用户。用户简档包括与用户相关的附加信息或与给予 用户的项目。 检索项目配置文件以确定哪些用户对特定项目进行了评级。 访问这些用户的配置文件，并使用等级来计算相对于其他用户的相似性因子。 有时与置信因子相关的相似性因子被用于选择一组邻近用户。 相邻用户基于它们各自的相似性因子进行加权，并且预测包含在该域中的项目的评级。 在一个实施例中，域中的项目具有特征。 在该实施例中，可以对特征值进行聚类，并且相似性因子包括分配的特征权重和特征值集群权重。 在一些实施例中，使用项目概念来增强推荐精度。
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