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    • 13. 发明授权
    • Systems and methods for providing recommendations based on collaborative and/or content-based nodal interrelationships
    • 基于协作和/或基于内容的节点相互关系提供建议的系统和方法
    • US08756187B2
    • 2014-06-17
    • US13919301
    • 2013-06-17
    • Nara Logics, Inc.
    • Nathan R. WilsonEmily A. HueskeThomas C. Copeman
    • G06N5/02G06Q30/02
    • G06N5/04G06N3/02G06N5/02G06N5/022G06Q20/203G06Q30/02G06Q30/0269G06Q30/0282H04L67/22
    • In selected embodiments a recommendation generator builds a network of interrelationships between venues, reviewers and users based on their attributes and reviewer and user reviews of the venues. Each interrelationship or link may be positive or negative and may accumulate with other links (or anti-links) to provide nodal links the strength of which are based on commonality of attributes among the linked nodes and/or common preferences that one node, such as a reviewer, expresses for other nodes, such as venues. The links may be first order (based on a direct relationship between, for instance, a reviewer and a venue) or higher order (based on, for instance, the fact that two venue are both liked by a given reviewer). The recommendation engine in certain embodiments determines recommended venues based on user attributes and venue preferences by aggregating the link matrices and determining the venues which are most strongly coupled to the user.
    • 在选择的实施例中,推荐生成器基于场馆的属性和评论者以及用户的评论构建场馆,评论者和用户之间的相互关系的网络。 每个相互关系或链接可以是正的或负的,并且可以与其他链接(或反链接)累积以提供节点链接,其节点链接的强度基于链接的节点之间的属性的共同性和/或一个节点的共同偏好,诸如 评论者,表达其他节点,如场地。 链接可以是第一顺序(基于例如审阅者和场地之间的直接关系)或更高的顺序(例如,基于例如两个场所都被给定的评论者所喜欢的事实)。 某些实施例中的推荐引擎通过聚合链接矩阵并确定与用户最强耦合的场所,基于用户属性和场地偏好确定推荐场馆。
    • 15. 发明申请
    • SYSTEMS AND METHODS FOR PROVIDING RECOMMENDATIONS BASED ON COLLABORATIVE AND/OR CONTENT-BASED NODAL INTERRELATIONSHIPS
    • 基于协同和/或内容的NODAL中断提供建议的系统和方法
    • US20150220836A1
    • 2015-08-06
    • US14687742
    • 2015-04-15
    • NARA LOGICS, INC.
    • Nathan R. WILSONEmily A. HueskeThomas C. Copeman
    • G06N5/02G06Q30/06
    • In selected embodiments a recommendation generator builds a network of interrelationships between venues, reviewers and users based on their attributes and reviewer and user reviews of the venues. Each interrelationship or link may be positive or negative and may accumulate with other links (or anti-links) to provide nodal links the strength of which are based on commonality of attributes among the linked nodes and/or common preferences that one node, such as a reviewer, expresses for other nodes, such as venues. The links may be first order (based on a direct relationship between, for instance, a reviewer and a venue) or higher order (based on, for instance, the fact that two venue are both liked by a given reviewer). The recommendation engine in certain embodiments determines recommended venues based on user attributes and venue preferences by aggregating the link matrices and determining the venues which are most strongly coupled to the user.
    • 在选择的实施例中,推荐生成器基于场馆的属性和评论者以及用户的评论构建场馆,评论者和用户之间的相互关系的网络。 每个相互关系或链接可以是正的或负的,并且可以与其他链接(或反链接)累积以提供节点链接,其节点链接的强度基于链接的节点之间的属性的共同性和/或一个节点的共同偏好,诸如 评论者,表达其他节点,如场地。 链接可以是第一顺序(基于例如审阅者和场地之间的直接关系)或更高的顺序(例如,基于例如两个场所都被给定的评论者所喜欢的事实)。 某些实施例中的推荐引擎通过聚合链接矩阵并确定与用户最强耦合的场所,基于用户属性和场地偏好确定推荐场馆。