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1. 发明授权

US07904448B2 Incremental update of long-term and short-term user profile scores in a behavioral targeting system 有权
标题翻译：在行为定位系统中增加长期和短期用户配置文件分数
公开(公告)号：US07904448B2
公开(公告)日：2011-03-08
申请号：US11394358
申请日：2006-03-29
申请人： Christina Yip Chung , Abhinav Gupta , Joshua M. Koran , Long-Ji Lin , Hongfeng Yin
发明人： Christina Yip Chung , Abhinav Gupta , Joshua M. Koran , Long-Ji Lin , Hongfeng Yin
IPC分类号： G06F7/00
CPC分类号： G06Q30/02
摘要： A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.
摘要翻译：行为定位系统从在线活动确定用户个人资料。该系统包括多个模型，其定义用于确定用户简档分数的参数。事件信息，包括用户的在线活动，在一个实体被接收。要生成用户配置文件分数，选择一个模型。该模型包括新近度，强度和频率尺寸参数。行为定位系统为目标目标生成用户简档分数，例如品牌广告或直接响应广告。应用来自模型的参数以在类别中生成用户简档分数。行为定位系统具有在在线用户的广告投放中使用的应用。

2. 发明授权

US08504575B2 Behavioral targeting system 有权
标题翻译：行为定位系统
公开(公告)号：US08504575B2
公开(公告)日：2013-08-06
申请号：US11394343
申请日：2006-03-29
申请人： Joshua M. Koran , Christina Yip Chung , Abhinav Gupta , George H. John , Hongfeng Yin , Long-Ji Lin , Richard Frankel
发明人： Joshua M. Koran , Christina Yip Chung , Abhinav Gupta , George H. John , Hongfeng Yin , Long-Ji Lin , Richard Frankel
IPC分类号： G06F17/30
CPC分类号： G06Q30/0255 , G06F17/3053 , G06F17/30702 , G06F17/30761 , G06F17/30914 , G06N5/02 , G06Q10/067 , G06Q30/02
摘要： A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.
摘要翻译：行为定位系统从在线活动确定用户个人资料。该系统包括多个模型，其定义用于确定用户简档分数的参数。事件信息，包括用户的在线活动，在一个实体被接收。要生成用户配置文件分数，选择一个模型。该模型包括新近度，强度和频率尺寸参数。行为定位系统为目标目标生成用户简档分数，例如品牌广告或直接响应广告。应用来自模型的参数以在类别中生成用户简档分数。行为定位系统具有在在线用户的广告投放中使用的应用。

3. 发明申请

US20110161331A1 Incremental Update Of Long-Term And Short-Term User Profile Scores In A Behavioral Targeting System 审中-公开
标题翻译：长期和短期用户配置文件在行为定位系统中的增量更新
公开(公告)号：US20110161331A1
公开(公告)日：2011-06-30
申请号：US13010605
申请日：2011-01-20
申请人： Christina Yip Chung , Abbinav Gupta , Joshua M. Koran , Long-Ji Lin , Hongfeng Yin
发明人： Christina Yip Chung , Abbinav Gupta , Joshua M. Koran , Long-Ji Lin , Hongfeng Yin
IPC分类号： G06F17/30
CPC分类号： G06Q30/02
摘要： A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.
摘要翻译：行为定位系统从在线活动确定用户个人资料。该系统包括多个模型，其定义用于确定用户简档分数的参数。事件信息，包括用户的在线活动，在一个实体被接收。要生成用户配置文件分数，选择一个模型。该模型包括近似度，强度和频率尺寸参数。行为定位系统为目标目标生成用户简档分数，例如品牌广告或直接响应广告。应用来自模型的参数以在类别中生成用户简档分数。行为定位系统具有在在线用户的广告投放中使用的应用。

4. 发明授权

US07809740B2 Model for generating user profiles in a behavioral targeting system 有权
标题翻译：用于在行为定位系统中生成用户配置文件的模型
公开(公告)号：US07809740B2
公开(公告)日：2010-10-05
申请号：US11394374
申请日：2006-03-29
申请人： Christina Yip Chung , Joshua M. Koran , Long-Ji Lin , Hongfeng Yin
发明人： Christina Yip Chung , Joshua M. Koran , Long-Ji Lin , Hongfeng Yin
IPC分类号： G06F17/30
CPC分类号： G06Q30/02
摘要： A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.
摘要翻译：行为定位系统从在线活动确定用户个人资料。该系统包括多个模型，其定义用于确定用户简档分数的参数。事件信息，包括用户的在线活动，在一个实体被接收。要生成用户配置文件分数，选择一个模型。该模型包括新近度，强度和频率尺寸参数。行为定位系统为目标目标生成用户简档分数，例如品牌广告或直接响应广告。应用来自模型的参数以在类别中生成用户简档分数。行为定位系统具有在在线用户的广告投放中使用的应用。

5. 发明授权

US08438170B2 Behavioral targeting system that generates user profiles for target objectives 有权
公开(公告)号：US08438170B2
公开(公告)日：2013-05-07
申请号：US11394332
申请日：2006-03-29
申请人： Joshua M. Koran , Christina Yip Chung , Long-Ji Lin , Hongfeng Yin
发明人： Joshua M. Koran , Christina Yip Chung , Long-Ji Lin , Hongfeng Yin
IPC分类号： G06F17/30
CPC分类号： G06F17/30528 , G06F17/30294 , G06F17/30587 , G06F17/30876 , G06Q30/02 , G06Q30/0224 , G06Q30/0251
摘要： A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.

6. 发明申请

US20070260624A1 Incremental update of long-term and short-term user profile scores in a behavioral targeting system 有权
标题翻译：在行为定位系统中增加长期和短期用户配置文件分数
公开(公告)号：US20070260624A1
公开(公告)日：2007-11-08
申请号：US11394358
申请日：2006-03-29
申请人： Christina Chung , Abhinav Gupta , Joshua Koran , Long-Ji Lin , Hongfeng Yin
发明人： Christina Chung , Abhinav Gupta , Joshua Koran , Long-Ji Lin , Hongfeng Yin
IPC分类号： G06F7/00
CPC分类号： G06Q30/02
摘要： A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.
摘要翻译：行为定位系统从在线活动确定用户个人资料。该系统包括多个模型，其定义用于确定用户简档分数的参数。事件信息，包括用户的在线活动，在一个实体被接收。要生成用户配置文件分数，选择一个模型。该模型包括近似度，强度和频率尺寸参数。行为定位系统为目标目标生成用户简档分数，例如品牌广告或直接回应广告。应用来自模型的参数以在类别中生成用户简档分数。行为定位系统具有在在线用户的广告投放中使用的应用。

7. 发明申请

US20070260596A1 Behavioral targeting system 有权
标题翻译：行为定位系统
公开(公告)号：US20070260596A1
公开(公告)日：2007-11-08
申请号：US11394343
申请日：2006-03-29
申请人： Joshua Koran , Christina Chung , Abhinav Gupta , George John , Hongfeng Yin , Long-Ji Lin , Richard Frankel
发明人： Joshua Koran , Christina Chung , Abhinav Gupta , George John , Hongfeng Yin , Long-Ji Lin , Richard Frankel
IPC分类号： G06F17/30
CPC分类号： G06Q30/0255 , G06F17/3053 , G06F17/30702 , G06F17/30761 , G06F17/30914 , G06N5/02 , G06Q10/067 , G06Q30/02
摘要： A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.
摘要翻译：行为定位系统从在线活动确定用户个人资料。该系统包括多个模型，其定义用于确定用户简档分数的参数。事件信息，包括用户的在线活动，在一个实体被接收。要生成用户配置文件分数，选择一个模型。该模型包括新近度，强度和频率尺寸参数。行为定位系统为目标目标生成用户简档分数，例如品牌广告或直接响应广告。应用来自模型的参数以在类别中生成用户简档分数。行为定位系统具有在在线用户的广告投放中使用的应用。

8. 发明申请

US20080120339A1 Collaborative-filtering contextual model optimized for an objective function for recommending items 有权
标题翻译：针对推荐项目的目标函数优化的协同过滤上下文模型
公开(公告)号：US20080120339A1
公开(公告)日：2008-05-22
申请号：US11601447
申请日：2006-11-17
申请人： Wei Guan , Christina Yip Chung , Long-Ji Lin
发明人： Wei Guan , Christina Yip Chung , Long-Ji Lin
IPC分类号： G06F17/30
CPC分类号： G06Q30/02 , G06Q10/10 , Y10S707/99931 , Y10S707/99932 , Y10S707/99945
摘要： Methods and apparatus for a recommendation system based on collaborative filtering is provided. Explicit and implicit ratings of items by network users are used to create a contextual model. The explicit ratings comprise different rating types regarding different item attributes. The implicit ratings comprise different rating types derived from different user events and may include recency, intensity, or frequency ratings. The contextual model may be optimized for a specific objective function, such as click-through-rate or conversion rate. In other embodiments, item information is used to produce a content model where item information for an item is encoded as metadata into a document that represents the item. The contextual or content model is used to recommend one or more items to a current user. The basic unit of the recommendation system may be an item set of two or more items or a particular sequence of two or more items.
摘要翻译：提供了基于协同过滤的推荐系统的方法和装置。网络用户对项目的明确和隐含的评级用于创建上下文模型。明确的评级包括关于不同项目属性的不同评级类型。隐性评级包括从不同用户事件导出的不同评级类型，并且可以包括新近度，强度或频率等级。可以为特定目标函数优化上下文模型，例如点击率或转换率。在其他实施例中，项目信息用于产生内容模型，其中用于项目的项目信息被编码为代表项目的文档中的元数据。上下文或内容模型用于向当前用户推荐一个或多个项目。推荐系统的基本单元可以是两个或多个项目的项目集合或两个或更多个项目的特定序列。

9. 发明授权

US07590616B2 Collaborative-filtering contextual model based on explicit and implicit ratings for recommending items 有权
标题翻译：基于明确和隐含的推荐项目评级的协同过滤上下文模型
公开(公告)号：US07590616B2
公开(公告)日：2009-09-15
申请号：US11601449
申请日：2006-11-17
申请人： Wei Guan , Christina Yip Chung , Long-Ji Lin
发明人： Wei Guan , Christina Yip Chung , Long-Ji Lin
IPC分类号： G06F17/30
CPC分类号： G06F17/30867 , G06Q30/02 , G06Q30/06 , Y10S707/99932 , Y10S707/99936 , Y10S707/99937 , Y10S707/99945
摘要： Methods and apparatus for a recommendation system based on collaborative filtering is provided. Explicit and implicit ratings of items by network users are used to create a contextual model. The explicit ratings comprise different rating types regarding different item attributes. The implicit ratings comprise different rating types derived from different user events and may include recency, intensity, or frequency ratings. The contextual model may be optimized for a specific objective function, such as click-through-rate or conversion rate. In other embodiments, item information is used to produce a content model where item information for an item is encoded as metadata into a document that represents the item. The contextual or content model is used to recommend one or more items to a current user. The basic unit of the recommendation system may be an item set of two or more items or a particular sequence of two or more items.
摘要翻译：提供了基于协同过滤的推荐系统的方法和装置。网络用户对项目的明确和隐含的评级用于创建上下文模型。明确的评级包括关于不同项目属性的不同评级类型。隐性评级包括从不同用户事件导出的不同评级类型，并且可以包括新近度，强度或频率等级。可以为特定目标函数优化上下文模型，例如点击率或转换率。在其他实施例中，项目信息用于产生内容模型，其中用于项目的项目信息被编码为代表项目的文档中的元数据。上下文或内容模型用于向当前用户推荐一个或多个项目。推荐系统的基本单元可以是两个或多个项目的项目集合或两个或更多个项目的特定序列。

10. 发明授权

US07584171B2 Collaborative-filtering content model for recommending items 有权
标题翻译：用于推荐项目的协作过滤内容模型
公开(公告)号：US07584171B2
公开(公告)日：2009-09-01
申请号：US11601450
申请日：2006-11-17
申请人： Wei Guan , Christina Yip Chung , Long-Ji Lin
发明人： Wei Guan , Christina Yip Chung , Long-Ji Lin
IPC分类号： G06F17/30
CPC分类号： G06Q30/02 , G06F17/30867 , Y10S707/99932 , Y10S707/99936 , Y10S707/99937 , Y10S707/99945
摘要： Methods and apparatus for a recommendation system based on collaborative filtering is provided. Explicit and implicit ratings of items by network users are used to create a contextual model. The explicit ratings comprise different rating types regarding different item attributes. The implicit ratings comprise different rating types derived from different user events and may include recency, intensity, or frequency ratings. The contextual model may be optimized for a specific objective function, such as click-through-rate or conversion rate. In other embodiments, item information is used to produce a content model where item information for an item is encoded as metadata into a document that represents the item. The contextual or content model is used to recommend one or more items to a current user. The basic unit of the recommendation system may be an item set of two or more items or a particular sequence of two or more items.
摘要翻译：提供了基于协同过滤的推荐系统的方法和装置。网络用户对项目的明确和隐含的评级用于创建上下文模型。明确的评级包括关于不同项目属性的不同评级类型。隐性评级包括从不同用户事件导出的不同评级类型，并且可以包括新近度，强度或频率等级。可以为特定目标函数优化上下文模型，例如点击率或转换率。在其他实施例中，项目信息用于产生内容模型，其中用于项目的项目信息被编码为代表项目的文档中的元数据。上下文或内容模型用于向当前用户推荐一个或多个项目。推荐系统的基本单元可以是两个或多个项目的项目集合或两个或更多个项目的特定序列。

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