Method and apparatus for efficiently recommending items using automated
collaborative filtering and feature-guided automated collaborative
filtering
    3.
    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

    IPC分类号: G06F17/30 G06Q30/00 G06F19/00

    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。

    Computer-implemented collaborative filtering based method for
recommending an item to a user
    4.
    发明授权
    Computer-implemented collaborative filtering based method for recommending an item to a user 失效
    基于计算机实现的基于协作过滤的方法,用于向用户推荐项目

    公开(公告)号:US6049777A

    公开(公告)日:2000-04-11

    申请号:US818515

    申请日:1997-03-14

    IPC分类号: G06F17/30 G06Q30/00 G06F17/60

    摘要: An object for providing isolated, hierarchical data storage can be used in a method for recommending an item to one of a plurality of users. The data object abstracts an associated physical memory element and provides an interface for storing data and retrieving data from the physical memory element. In some embodiments the data object is provided with an indicator for identifying another data object that is used if a memory request is unable to be serviced by the associated physical memory element. In other embodiments this data object can be used to efficiently and transparently store profile data associated with a system for recommending items to users.

    摘要翻译: 用于提供隔离的层级数据存储的对象可以用于将项目推荐给多个用户之一的方法。 数据对象抽取相关联的物理存储器元件,并提供用于存储数据和从物理存储器元件检索数据的接口。 在一些实施例中,数据对象被提供有用于识别如果存储器请求不能被相关联的物理存储器元件服务的则使用的另一数据对象的指示符。 在其他实施例中,该数据对象可以用于有效和透明地存储与用于向用户推荐项目的系统相关联的简档数据。