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    • 22. 发明授权
    • Collaborative filtering
    • 协同过滤
    • US08135718B1
    • 2012-03-13
    • US11676264
    • 2007-02-16
    • Abhinandan S. DasAshutosh GargMayur Datar
    • Abhinandan S. DasAshutosh GargMayur Datar
    • G06F7/00G06F17/30
    • G06F17/30699G06F17/30598G06F17/30979
    • Systems, methods, and apparatus, including computer program products, for collaborative filtering are provided. A method is provided. The method includes clustering a plurality of entities with respect to one or more latent variables in a probability distribution model of a relationship between a set of entities and a set of items, the probability distribution model comprising a probability distribution of the set of items with respect to the latent variables. The method also includes, as new items are added to the set of items, updating the probability distribution of the set of the items with respect to the latent variables, and generating an updated relationship score for an entity with respect to the set of items based on the entity's fractional membership in the clustering with respect to the latent variables and based on the updated probability distribution of the set of the items with respect to the latent variables.
    • 提供了用于协同过滤的系统,方法和装置,包括计算机程序产品。 提供了一种方法。 该方法包括在一组实体与一组项目之间的关系的概率分布模型中相对于一个或多个潜在变量聚类多个实体,所述概率分布模型包括所述一组项目的概率分布 到潜在变量。 该方法还包括,当新项目被添加到该组项目中时,相对于潜在变量更新项目组的概率分布,并且相对于该组项目生成关于实体的更新关系得分 关于实体关于潜在变量的聚类中的分数成员,并且基于相对于潜在变量的项目集合的更新的概率分布。
    • 23. 发明授权
    • Scalable user clustering based on set similarity
    • 基于集合相似度的可扩展用户群集
    • US07962529B1
    • 2011-06-14
    • US12774775
    • 2010-05-06
    • Mayur DatarAshutosh Garg
    • Mayur DatarAshutosh Garg
    • G06F7/00G06F17/30
    • G06Q30/02G06F17/30867
    • Methods and apparatus, including systems and computer program products, to provide clustering of users in which users are each represented as a set of elements representing items, e.g., items selected by users using a system. In one aspect, a program operates to obtain a respective interest set for each of multiple users, each interest set representing items in which the respective user expressed interest; for each of the users, to determine k hash values of the respective interest set, wherein the i-th hash value is a minimum value under a corresponding i-th hash function; and to assign each of the multiple users to each of the respective k clusters established for the respective user, the i-th cluster being represented by the i-th hash value. The assignment of each of the users to k clusters is done without regard to the assignment of any of the other users to k clusters.
    • 方法和装置,包括系统和计算机程序产品,用于提供用户的聚类,其中每个用户被表示为表示项目的一组元素,例如由使用系统的用户选择的项目。 在一个方面中,程序运行以获得针对多个用户中的每一个的各自的兴趣集合,每个兴趣集合表示相应用户表示兴趣的项目; 对于每个用户,确定相应兴趣集的k个哈希值,其中第i个散列值是相应的第i个散列函数下的最小值; 并且将多个用户中的每一个分配给为各个用户建立的各个k个集群中的每一个,第i个集群由第i个散列值表示。 完成每个用户到k个集群的分配,而不考虑将任何其他用户分配给k个集群。
    • 27. 发明授权
    • Collaborative filtering
    • 协同过滤
    • US08407226B1
    • 2013-03-26
    • US13039173
    • 2011-03-02
    • Abhinandan S. DasAshutosh GargMayur Datar
    • Abhinandan S. DasAshutosh GargMayur Datar
    • G06F7/00G06F17/30
    • G06F17/30867
    • Systems, methods, and apparatus, including computer program products, for collaborative filtering are provided. In one implementation, a computer-implemented method is provided. The method includes receiving a shard of data representing a subset of a set of entities and a subset of a set of items, generating an iteration of a maximum likelihood estimate of a probability distribution model of a relationship between the set of entities and the set of items, the probability distribution model comprising a probability distribution of the set of items with respect to latent variables and a probability distribution of the latent variables with respect to the set of users, and generating statistics from results from the generating step which are passed to different shards for use in a next iteration of the maximum likelihood estimate.
    • 提供了用于协同过滤的系统,方法和装置,包括计算机程序产品。 在一个实现中,提供了计算机实现的方法。 该方法包括:接收表示一组实体的子集的数据的碎片,以及一组项目的子集,生成一组实体之间的关系的概率分布模型的最大似然估计的迭代, 项目,概率分布模型包括相对于潜在变量的项目集合的概率分布以及潜在变量相对于用户集合的概率分布,以及从生成步骤的结果生成统计信息,该统计信息被传递给不同的 碎片用于最大似然估计的下一次迭代。
    • 28. 发明授权
    • Presenting a diversity of recommendations
    • 提出各种建议
    • US08065254B1
    • 2011-11-22
    • US12033540
    • 2008-02-19
    • Abhinandan S. DasAshutosh GargMayur Datar
    • Abhinandan S. DasAshutosh GargMayur Datar
    • G06F17/00G06N5/02
    • G06F17/30864
    • Methods, systems and apparatus, including computer program products, for providing a diversity of recommendations. According to one method, results are identified so as to increase the likelihood that at least one result will be of interest to a user. Following the identification of a first result, second and later results are identified based on an assumption that the previously identified results are not of interest to the user. The identification of diverse results can be based on formulas that approximate the probability or provide a likelihood score of a user selecting a given result, where a measured similarity between a given object and previously identified results tends to decrease the calculated probability approximation or likelihood score for that object.
    • 方法,系统和设备,包括计算机程序产品,用于提供多种建议。 根据一种方法,识别结果以便增加至少一个结果对用户感兴趣的可能性。 在识别出第一结果之后,基于以前认为的结果对用户不感兴趣的假设来识别第二和后续结果。 不同结果的识别可以基于近似概率或提供用户选择给定结果的似然分数的公式,其中给定对象和先前识别的结果之间的测量相似度倾向于降低计算的概率近似或似然分数 那个对象。
    • 29. 发明申请
    • SERVER-SIDE MATCH
    • 服务器端匹配
    • US20110276558A1
    • 2011-11-10
    • US13179705
    • 2011-07-11
    • Ashutosh GargMayur Datar
    • Ashutosh GargMayur Datar
    • G06F17/30
    • G06F16/24534
    • Systems and techniques for converting numeric queries into substantially equivalent textual queries are described. In general, the systems and techniques discussed use search query logs to accurately select a most probably mapping for a numeric-to-text conversion. This mapping can occur when a system (e.g., a server-side search system) receives a series of numeric inputs (e.g., from a cell phone keypad) that may correspond to more than one word. For example, a search server may receive input 22737, which corresponds to both the words ACRES and CASES, as part of a query. The server uses current entries in query logs to create mappings for words from the numeric input. If recent queries indicate that the term ACRES is currently more popular than the term CASES, the mapping may match the entry 22737 to the text ACRES.
    • 描述将数字查询转换成大致相等的文本查询的系统和技术。 一般来说,所讨论的系统和技术使用搜索查询日志准确地选择数字到文本转换的最可能的映射。 当系统(例如,服务器端搜索系统)接收到可能对应于多于一个字的一系列数字输入(例如,来自手机键盘)时,可以发生该映射。 例如,作为查询的一部分,搜索服务器可以接收对应于词汇ACRES和CASES的输入22737。 服务器使用查询日志中的当前条目为数字输入中的单词创建映射。 如果最近的查询表明术语ACRES目前比术语CASES更受欢迎,则该映射可以将条目22737与文本ACRES匹配。