公开(公告)号：US20160162975A1

公开(公告)日：2016-06-09

申请号：US14564123

申请日：2014-12-09

Applicant: Google Inc.

Inventor： Aiyou Chen ,  Jeffrey David Oldham

IPC: G06Q30/06 ,  G06N7/00

CPC classification number: G06Q30/0631 ,  G06N7/005

Abstract: Systems and methods of directed item consumption recommendations are disclosed which include generating, with a server, empirical transition matrix data that includes row data for a first item and column data for a second item, and an entry in the empirical transition matrix data for a number of users that acquire the second item after the first item, generating, with the server, metadata transition matrix data by partitioning items for each item metadata type, setting a uniform transition probability for all items in the partition, and summing the uniform transition probabilities across all metadata types, generating, with the server, transition probability matrix data by multiplying the metadata transition matrix data with a weight parameter, adding the result to the empirical transition matrix data, and normalizing each row, and providing item recommendations to a user computing device communicatively coupled to the server according to the generated transition probability matrix data.

Abstract translation: 公开了指导性项目消费推荐的系统和方法，其包括与服务器一起生成包括用于第一项目的行数据和第二项目的列数据的经验转换矩阵数据，以及用于数字的经验转移矩阵数据中的条目 在第一个项目之后获取第二个项目的用户，通过分配每个项目元数据类型的项目，通过服务器生成元数据转换矩阵数据，为分区中的所有项目设置均匀的转移概率，并将均匀转移概率相加 所有元数据类型，通过将元数据转换矩阵数据与权重参数相乘来产生与服务器的转移概率矩阵数据，将结果添加到经验转移矩阵数据中，并对每一行进行归一化，并向用户计算设备提供项目建议 根据所生成的转移概率矩阵数据通信地耦合到服务器 一个。

公开(公告)号：US20150186357A1

公开(公告)日：2015-07-02

申请号：US14144620

申请日：2013-12-31

Applicant: Google Inc.

Inventor： Jeffrey David Oldham ,  Mark Edward Davis ,  Chinglan Ho ,  Cibu Chalissery Johny ,  Markus Scherer ,  Jungshik Shin ,  Erik Menno van der Poel ,  Neha Chachra

IPC: G06F17/28

CPC classification number: G06F9/4448 ,  G06F9/454 ,  G06F17/275 ,  G10L15/005 ,  G10L15/22

Abstract: Described is a technique for establishing an interaction language for a user interface without having to communicate with the user in a default language, which the user may or may not understand. The technique may prompt the user for multiples responses in order to determine a specific language. The responses may include speech input or selecting particular regions on a map. In some implementations, the language may be precise to a particular dialect or variant preferred or spoken by the user. Accordingly, this approach provides an accurate and efficient method of providing a high degree of specificity for language selection without overwhelming the user with an unmanageable list of languages.

Abstract translation: 描述了用于为用户界面建立交互语言的技术，而不必以用户可能理解或可能不理解的默认语言与用户通信。 该技术可以提示用户多次响应以确定特定语言。 响应可以包括语音输入或选择地图上的特定区域。 在一些实现中，该语言可能对于用户优选或说出的特定方言或变体是精确的。 因此，这种方法提供了一种为语言选择提供高度特异性的准确和有效的方法，而不会使用户无法管理的语言列表。

公开(公告)号：US09304787B2

公开(公告)日：2016-04-05

申请号：US14144620

申请日：2013-12-31

Applicant: Google Inc.

Inventor： Jeffrey David Oldham ,  Mark Edward Davis ,  Chinglan Ho ,  Cibu Chalissery Johny ,  Markus Scherer ,  Jungshik Shin ,  Erik Menno van der Poel ,  Neha Chachra

IPC: G06F9/44 ,  G10L15/00 ,  G06F17/27

CPC classification number: G06F9/4448 ,  G06F9/454 ,  G06F17/275 ,  G10L15/005 ,  G10L15/22

Abstract: Described is a technique for establishing an interaction language for a user interface without having to communicate with the user in a default language, which the user may or may not understand. The technique may prompt the user for multiples responses in order to determine a specific language. The responses may include speech input or selecting particular regions on a map. In some implementations, the language may be precise to a particular dialect or variant preferred or spoken by the user. Accordingly, this approach provides an accurate and efficient method of providing a high degree of specificity for language selection without overwhelming the user with an unmanageable list of languages.

Abstract translation: 描述了用于为用户界面建立交互语言的技术，而不必以用户可能理解或可能不理解的默认语言与用户通信。 该技术可以提示用户多次响应以确定特定语言。 响应可以包括语音输入或选择地图上的特定区域。 在一些实现中，该语言可能对于用户优选或说出的特定方言或变体是精确的。 因此，这种方法提供了一种为语言选择提供高度特异性的准确和有效的方法，而不会使用户无法管理的语言列表。

公开(公告)号：US20150363802A1

公开(公告)日：2015-12-17

申请号：US14085086

申请日：2013-11-20

Applicant: Google Inc.

Inventor： Hal Ronald Varian ,  Seth Stephens-Davidowitz ,  Jeffrey David Oldham

IPC: G06Q30/02

CPC classification number: G06Q30/0203

Abstract: Survey accuracy of small sample sizes may be amplified by including, excluding, or weighting survey responses of respondents responsive to characteristics of the respondent being correlated with or not correlated with characteristics of the population determined from aggregated behavioral histories of the population, resulting in favoring survey results of individuals that are truly representative of the larger population and excluding results from outliers. Search queries from devices in a particular region may be aggregated to identify common searches, building a model of characteristics of the regional population without requiring any private or confidential data of the population. Surveys may be given to a small number of individuals in the region, and if the individual's characteristics match the modeled regional characteristics, then the individual's survey responses may be used to build a statistical estimate of responses from the region, at a higher degree of confidence than allowed by mere random sampling.

Abstract translation: 通过包括，排除或加权响应于受访者的特征的调查回答的调查准确性可以被放大，该受访者的特征与人口的聚合行为历史确定的人群特征相关或不相关，从而有利于调查 真正代表较大人口的个人的结果，并排除异常值的结果。 来自特定区域的设备的搜索查询可以被聚合以识别常见的搜索，构建区域人群的特征模型，而不需要人口的任何私人或机密数据。 可能会对该地区的少数个人进行调查，如果个人的特征与模拟的区域特征相匹配，那么可以使用个人的调查回答来建立来自该地区的反应的统计估计，在更高的信心度 比纯粹随机抽样所允许。