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1. 发明申请

US20150242906A1 GENERATING A SET OF RECOMMENDED NETWORK USER IDENTIFIERS FROM A FIRST SET OF NETWORK USER IDENTIFIERS AND ADVERTISER BID DATA 审中-公开
标题翻译：从第一组网络用户标识符和广告客户端数据生成一组建议的网络用户标识符
公开(公告)号：US20150242906A1
公开(公告)日：2015-08-27
申请号：US13462425
申请日：2012-05-02
申请人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
发明人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
IPC分类号： G06Q30/02
CPC分类号： G06Q30/0255 , G06Q30/0272 , G06Q30/0275 , G06Q30/0277 , H04L67/22
摘要： A computerized method, system for, and computer-readable medium operable to take a first set of network user identifiers and generate a set of recommended network user identifiers based on the first set and advertiser bid data. A processing circuit receives the first set and advertiser bid data for the first set and stores the first set and advertiser bid data for the first set in a memory. The advertiser bid data includes a price offered by the advertiser for the advertiser's content to be shown to a network user identifier in the first set. The processing circuit receives advertiser bid data for a second set. The processing circuit generates a user similarity parameter based on the advertiser bid data for the first set and the advertiser bid data for the second set. The processing circuit generates the set of recommended network user identifiers based on the user similarity parameter.
摘要翻译：一种计算机化方法，系统和计算机可读介质，其可操作以取得第一组网络用户标识符，并且基于第一集合和广告商出价数据生成一组推荐的网络用户标识符。处理电路接收第一集合的第一集合和广告商投标数据，并将第一集合的第一集合和广告商投标数据存储在存储器中。广告主的出价数据包括广告商为要在第一组中的网络用户标识符显示的广告主的内容提供的价格。处理电路接收第二组的广告商投标数据。处理电路基于第一组的广告商投标数据和第二组的广告商投标数据来生成用户相似性参数。处理电路根据用户相似性参数生成一组推荐的网络用户标识符。

2. 发明授权

US09053185B1 Generating a representative model for a plurality of models identified by similar feature data 有权
标题翻译：为由相似特征数据识别的多个模型生成代表性模型
公开(公告)号：US09053185B1
公开(公告)日：2015-06-09
申请号：US13460469
申请日：2012-04-30
申请人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
发明人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
IPC分类号： G06F17/00 , G06Q30/00 , G06F17/30 , G06Q30/02
CPC分类号： G06F17/30864 , G06Q30/0253 , G06Q30/0256 , G06Q30/0277
摘要： A computerized method for generating a representative model for a plurality of different models identified by similar feature data. A processing circuit receives a plurality of different models, each model configured for use in generating a second set of network user identifiers based on a first set of network user identifiers. The processing circuit receives feature data for each of the plurality of different models, each feature data having a corresponding feature weight data. The processing circuit identifies similar models within the plurality of different models based on a similarity of the feature data between models within the plurality of different models. The processing circuit generates the representative model to represent the similar models. The representative model may be used to generate the second set of network user identifiers based on the feature data and corresponding weight data of the representative model.
摘要翻译：一种用于生成由相似特征数据识别的多个不同模型的代表性模型的计算机化方法。处理电路接收多个不同的模型，每个模型被配置用于基于第一组网络用户标识符生成第二组网络用户标识符。处理电路接收多个不同模型中的每一个的特征数据，每个特征数据具有对应的特征权重数据。处理电路基于多个不同模型中的模型之间的特征数据的相似度来识别多个不同模型内的相似模型。处理电路生成代表性模型来表示相似的模型。代表性模型可以用于基于特征数据和代表性模型的对应权重数据来生成第二组网络用户标识符。

3. 发明授权

US08886575B1 Selecting an algorithm for identifying similar user identifiers based on predicted click-through-rate 有权
标题翻译：基于预测的点击率选择用于识别类似用户标识符的算法
公开(公告)号：US08886575B1
公开(公告)日：2014-11-11
申请号：US13534480
申请日：2012-06-27
申请人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
发明人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
IPC分类号： G06F15/18
CPC分类号： G06Q30/0201
摘要： A computerized method, system for, and computer-readable medium operable to select an algorithm for generating models configured to identify similar user identifiers. A first plurality of models generated by a first algorithm is received. A plurality of lists of similar user identifiers is generated. User queries associated with user identifiers on the plurality of lists of similar user identifiers are identified. Predicted click-through rates for the user queries is received. An average predicted click-through rate is computed for each model based on the predicted click-through rates. A weighted average predicted click-through rate associated with the first plurality of models is computed. The weighted average predicted click-through rate for the first plurality of models can be compared to a weighted average predicted click-through rate for a second plurality of models generated by a second algorithm. The algorithm for generating models is selected based on the comparison.
摘要翻译：一种计算机化方法，系统和计算机可读介质，其可操作以选择用于生成被配置为识别相似用户标识符的模型的算法。接收由第一算法生成的第一多个模型。生成多个相似用户标识符的列表。识别与多个相似用户标识符列表上的用户标识符相关联的用户查询。收到用户查询的预测点击率。根据预测的点击率计算每个模型的平均预测点击率。计算与第一多个模型相关联的加权平均预测点击率。可以将第一多个模型的加权平均预测点击率与由第二算法生成的第二多个模型的加权平均预测点击率进行比较。基于比较选择生成模型的算法。

4. 发明授权

US08572096B1 Selecting keywords using co-visitation information 有权
标题翻译：使用共同访问信息选择关键字
公开(公告)号：US08572096B1
公开(公告)日：2013-10-29
申请号：US13297544
申请日：2011-11-16
申请人： Rohan Seth , Shumeet Baluja , Dandapani Sivakumar , Deepak Ravichandran
发明人： Rohan Seth , Shumeet Baluja , Dandapani Sivakumar , Deepak Ravichandran
IPC分类号： G06F17/30
CPC分类号： G06F17/30867 , G06Q10/10
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting keywords for resources. In one aspect, a method includes identifying a particular online resource that includes non-text content. Co-visitation data are obtained for the particular resource. The co-visitation data specify one or more co-requested online resources for the particular online resource. Each of the co-requested online resources were requested by a user device within a threshold period of the request for the particular online resource by the user device. Keywords are identified for each of the co-requested online resources, and can include keywords that were selected based on text content of the co-requested online resource. One or more of the identified keywords are selected as keywords for the particular resource.
摘要翻译：方法，系统和装置，包括在计算机存储介质上编码的计算机程序，用于选择资源的关键字。一方面，一种方法包括识别包括非文本内容的特定在线资源。获取特定资源的共访问数据。共同访问数据指定特定在线资源的一个或多个共同请求的在线资源。在用户设备对特定在线资源的请求的阈值期间内，由用户设备请求每个共同请求的在线资源。针对每个共同请求的在线资源标识关键字，并且可以包括基于共同请求的在线资源的文本内容而选择的关键字。选择一个或多个所识别的关键词作为特定资源的关键字。

5. 发明授权

US09424342B1 Geographically local query detection 有权
标题翻译：地理位置查询检测
公开(公告)号：US09424342B1
公开(公告)日：2016-08-23
申请号：US12708583
申请日：2010-02-19
申请人： Deepak Ravichandran , Dandapani Sivakumar , Rohan Seth , Shumeet Baluja
发明人： Deepak Ravichandran , Dandapani Sivakumar , Rohan Seth , Shumeet Baluja
IPC分类号： G06F17/30
CPC分类号： G06F17/30637 , G06F17/3087
摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting local search queries. In one aspect, a method includes accessing a search query log that includes data specifying search queries corresponding to particular geographic regions and for at least one of the search queries corresponding to the particular geographic region generating a geo-query count that represents a total number of times that the search query was received over a specified period. The geo-query count is compared to a corresponding expected query count for the search query, where the expected query count is a baseline number of times that the query is expected to be received. In response to determining that the search query has a geo-query count that exceeds the corresponding expected query count by at least a threshold amount, the particular query is classified as a local query for the particular geographic region.
摘要翻译：方法，系统和装置，包括在计算机存储介质上编码的计算机程序，用于检测本地搜索查询。一方面，一种方法包括访问包括指定与特定地理区域相对应的搜索查询的数据的搜索查询日志，以及对应于特定地理区域的搜索查询中的至少一个生成地理查询计数，所述地理查询计数表示总数在指定时间段内收到搜索查询的时间。将地理查询计数与搜索查询的相应预期查询计数进行比较，其中预期查询计数是希望接收查询的基准次数。响应于确定搜索查询具有超过相应的预期查询计数至少阈值量的地理查询计数，特定查询被分类为特定地理区域的本地查询。

6. 发明授权

US08914500B1 Creating a classifier model to determine whether a network user should be added to a list 有权
标题翻译：创建分类器模型以确定是否应将网络用户添加到列表中
公开(公告)号：US08914500B1
公开(公告)日：2014-12-16
申请号：US13476532
申请日：2012-05-21
申请人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
发明人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
IPC分类号： G06F15/173
CPC分类号： G06Q30/0269
摘要： A computerized method of creating a classifier model to determine whether a network user should be added to a list of similar network users. A first list of network users, a second list of network users who are not on the first list of network users and characteristic data associated with the network users' network activity are received. A time period is designated. A first category of network activities performed by a network user on the first list within the designated time period is identified. A second category of network activities performed at any time by network users on the second list is identified. A third category of network activities performed by network users on the first list at a time outside of the designated time period is identified. The classifier model is generated based on the first, second and third categories of network activities.
摘要翻译：一种创建分类器模型以确定是否应将网络用户添加到类似网络用户列表的计算机化方法。网络用户的第一个列表，不在网络用户的第一个列表中的网络用户的第二个列表以及与网络用户的网络活动相关联的特征数据。指定一个时间段。识别网络用户在指定时间段内在第一列表上执行的第一类网络活动。识别网络用户在第二个列表中随时执行的第二类网络活动。识别网络用户在指定时间段之外的第一个列表上执行的第三类网络活动。分类器模型基于第一，第二和第三类网络活动生成。

7. 发明授权

US09065727B1 Device identifier similarity models derived from online event signals 有权
标题翻译：从在线事件信号导出的设备标识符相似性模型
公开(公告)号：US09065727B1
公开(公告)日：2015-06-23
申请号：US13601775
申请日：2012-08-31
申请人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
发明人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
IPC分类号： G06F15/173 , H04L12/26
CPC分类号： H04L43/04 , G06Q30/06 , H04L67/22
摘要： A computerized method and system operable to build a device identifier similarity model with online event signals and determine similar network device identifiers. A processing circuit receives a first set of network device identifiers. The processing circuit represents each network device identifier of the first set by feature data associated with each network device identifier's network activity, where the feature data is associated with the content clicked-on or converted-on. The processing circuit applies abstractions on the feature data to form concepts. The processing circuit derives at least one hierarchy of feature data based on the keywords and concepts of the feature data. The processing circuit expands the feature data based on the derived at least one hierarchy of feature data and generates the device identifier similarity model based on the expanded feature data. The processing circuit is also capable of determining long-term and short-term history events.
摘要翻译：一种计算机化方法和系统，其可操作以用在线事件信号构建设备标识符相似性模型并确定类似的网络设备标识符。处理电路接收第一组网络设备标识符。处理电路通过与每个网络设备标识符的网络活动相关联的特征数据来表示第一组的每个网络设备标识符，其中特征数据与点击或转换的内容相关联。处理电路对特征数据应用抽象以形成概念。处理电路根据特征数据的关键词和概念，产生至少一个特征数据层级。处理电路基于导出的特征数据的至少一个层次扩展特征数据，并且基于扩展的特征数据生成设备标识符相似性模型。处理电路还能够确定长期和短期历史事件。

8. 发明授权

US08527526B1 Selecting a list of network user identifiers based on long-term and short-term history data 有权
标题翻译：根据长期和短期历史数据选择网络用户标识符列表
公开(公告)号：US08527526B1
公开(公告)日：2013-09-03
申请号：US13462130
申请日：2012-05-02
申请人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
发明人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
IPC分类号： G06F7/00
CPC分类号： G06Q30/0277
摘要： A computerized method, system for, and computer-readable medium operable to select a list of network user identifiers. A processing circuit receives a list of network user identifiers represented by long-term history data indicative of web pages visited prior to a first time and short-term history data indicative of web pages visited after the first time and prior to a second time. Long-term interest categories, corresponding weight values for each long-term interest category, short-term interest categories and corresponding weight values for each short-term interest category are identified. A model comprising the long-term and short-term interest categories is generated based on the weight values of the long-term and short-term interest categories using either arithmetic or harmonic progression. The processing circuit receives a list of candidate network user identifiers and generates a list of similar network user identifiers based on the model.
摘要翻译：用于选择网络用户标识符列表的计算机化方法，系统和计算机可读介质。处理电路接收由指示在第一时间之前访问的网页的长期历史数据表示的网络用户标识符的列表，以及指示在第一次和第二次之前访问的网页的短期历史数据。确定每个短期利益类别的长期利益类别，每个长期利益类别的相应权重值，短期利益类别和相应的权重值。包括长期和短期兴趣类别的模型是基于使用算术或谐波进行的长期和短期兴趣类别的权重值生成的。处理电路接收候选网络用户标识符的列表，并且基于该模型生成类似的网络用户标识符的列表。

9. 发明授权

US08856131B1 Computer networked selecting of consumer interests 有权
标题翻译：计算机联网选择消费者利益
公开(公告)号：US08856131B1
公开(公告)日：2014-10-07
申请号：US13523616
申请日：2012-06-14
申请人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
发明人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
IPC分类号： G06F7/04 , G06F17/30
CPC分类号： G06F17/30867 , G06Q30/02
摘要： Systems and methods of selecting consumers to receive content on a computer network are provided. A user list identifying a first plurality of users having a group of features corresponding to internet activity of the first plurality of users can be obtained at a computing device. A subgroup of features can be selected from the group of features, and a cluster of users of the first plurality of users can be identified. The users of the cluster of users can each have at least one feature of the subgroup of features. A supplemental user having a supplemental feature can be identified. A correlation between the supplemental feature and at least one feature of the subgroup of features can be determined, and an expanded user list that includes at least one of the first plurality of users and the supplemental user can be generated.
摘要翻译：提供了选择消费者在计算机网络上接收内容的系统和方法。可以在计算设备处获得识别具有与第一多个用户的互联网活动相对应的特征组的第一多个用户的用户列表。可以从特征组中选择特征的子组，并且可以识别第一多个用户的一群用户。用户群集的用户可以各自具有该特征子组的至少一个特征。可以识别具有补充特征的补充用户。可以确定补充特征与特征子组的至少一个特征之间的相关性，并且可以生成包括第一多个用户和补充用户中的至少一个的扩展用户列表。

10. 发明授权

US08874589B1 Adjust similar users identification based on performance feedback 有权
标题翻译：根据性能反馈调整类似的用户识别
公开(公告)号：US08874589B1
公开(公告)日：2014-10-28
申请号：US13550073
申请日：2012-07-16
申请人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
发明人： Jia Liu , Yijian Bai , Manojav Patil , Deepak Ravichandran , Sittichai Jiampojamarn , Shankar Ponnekanti
IPC分类号： G06F17/30
CPC分类号： G06F17/30867
摘要： A method of setting a threshold similarity score value for a first plurality of network user identifiers. The first plurality of network user identifiers, a second plurality of network user identifiers and characteristic data associated with the network user identifiers is received. A performance target and an experimental threshold similarity score value are designated. A similarity score between the first and second plurality of network user identifiers is calculated. Performance statistics data for each of the second plurality of network user identifiers having a similarity score greater than or equal to the experimental threshold similarity score value is collected and compared to the similarity score of the network user identifier. Based on the comparison, the experimental threshold similarity score value is adjusted to a similarity score value that achieves the performance target and the threshold similarity score value is set to the adjusted experimental threshold similarity score value.
摘要翻译：一种为第一多个网络用户标识符设置阈值相似度得分值的方法。接收第一多个网络用户标识符，第二多个网络用户标识符和与网络用户标识符相关联的特征数据。指定性能目标和实验阈值相似性得分值。计算第一和第二多个网络用户标识符之间的相似度分数。收集具有大于或等于实验阈值相似性得分值的相似度得分的第二多个网络用户标识符中的每一个的性能统计数据，并与网络用户标识符的相似性得分进行比较。基于比较，将实验阈值相似性得分值调整为达到性能目标的相似性得分值，并将阈值相似性得分值设置为调整后的实验阈值相似性得分值。

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