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1.发明授权Recommendation agent using a personality model determined from mobile device data 有权使用从移动设备数据确定的个性模型的推荐代理公开(公告)号：US09020864B2
公开(公告)日：2015-04-28
申请号：US13950117
申请日：2013-07-24
申请人： ARO, Inc.
CPC分类号： G06N5/04 , G06F17/2785 , G06F17/30876 , G06N5/02 , G06N99/005 , G06Q30/0631 , H04W4/02 , H04W4/21
摘要： A user's context history is analyzed to build a personality model describing the user's personality and interests. The personality model includes a plurality of metrics indicating the user's position on a plurality of personality dimensions, such as desire for novelty, tendency for extravagance, willingness to travel, love of the outdoors, preference for physical activity, and desire for solitude. A customized recommendation agent is then built based on the personality model, which selects a recommendation from a corpus to present to the user based on an affinity between the user's personality and the selected recommendation.
摘要翻译： 分析用户的上下文历史，构建描述用户个性和兴趣的个性模型。 个性模型包括指示用户在多个个性维度上的位置的多个度量，诸如欲望的新颖性，奢侈的倾向，旅行意愿，对户外的爱，体育活动的偏爱以及对孤独的渴望。 然后，基于人格模型构建定制推荐代理，该个性模型基于用户的个性与所选择的推荐之间的亲和度，从语料库中选择推荐给用户。
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2.发明申请RECOMMENDATION AGENT USING A PERSONALITY MODEL DETERMINED FROM MOBILE DEVICE DATA 有权使用移动设备数据确定的个性化模型的建议代理公开(公告)号：US20140032452A1
公开(公告)日：2014-01-30
申请号：US13950117
申请日：2013-07-24
申请人： ARO, Inc.
CPC分类号： G06N5/04 , G06F17/2785 , G06F17/30876 , G06N5/02 , G06N99/005 , G06Q30/0631 , H04W4/02 , H04W4/21
摘要： A user's context history is analyzed to build a personality model describing the user's personality and interests. The personality model includes a plurality of metrics indicating the user's position on a plurality of personality dimensions, such as desire for novelty, tendency for extravagance, willingness to travel, love of the outdoors, preference for physical activity, and desire for solitude. A customized recommendation agent is then built based on the personality model, which selects a recommendation from a corpus to present to the user based on an affinity between the user's personality and the selected recommendation.
摘要翻译： 分析用户的上下文历史，构建描述用户个性和兴趣的个性模型。 个性模型包括指示用户在多个个性维度上的位置的多个度量，诸如欲望的新颖性，奢侈的倾向，旅行意愿，对户外的爱，体育活动的偏爱以及对孤独的渴望。 然后，基于人格模型构建定制推荐代理，该个性模型基于用户的个性与所选择的推荐之间的亲和度，从语料库中选择推荐给用户。
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公开(公告)号：US20140032453A1
公开(公告)日：2014-01-30
申请号：US13950224
申请日：2013-07-24
申请人： ARO, Inc.
发明人： Kevin Francis Eustice , Alan Linchuan Liu , Michael Perkowitz , Andrew F. Hickl , Paul G. Allen
IPC分类号： G06N5/02
CPC分类号： G06N5/04 , G06F17/2785 , G06F17/30876 , G06N5/02 , G06N99/005 , G06Q30/0631 , H04W4/02 , H04W4/21
摘要： A user's context history is used to help select contextual information to provide to the user. Context data describing the user's current context is received and a plurality of information items corresponding to the user's current context are identified from a contextual information corpus. A personalized user behavior model for the user is applied to determine the likelihood that each of the identified information items will be of value to the user. One or more of the information items are selected based on the corresponding likelihoods and the selected information items are provided for presentation to the user.
摘要翻译： 用户的上下文历史用于帮助选择提供给用户的上下文信息。 接收描述用户当前上下文的上下文数据，并从上下文信息语料库中识别与用户当前上下文相对应的多个信息项。 应用用于用户的个性化用户行为模型来确定每个所识别的信息项对用户来说是有价值的可能性。 基于相应的可能性来选择信息项中的一个或多个，并且提供所选择的信息项以呈现给用户。
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4.发明申请RECOMMENDATION AGENT USING A PERSONALITY MODEL DETERMINED FROM MOBILE DEVICE DATA 审中-公开使用移动设备数据确定的个性化模型的建议代理公开(公告)号：US20150170042A1
公开(公告)日：2015-06-18
申请号：US14629456
申请日：2015-02-23
申请人： ARO, Inc.
CPC分类号： G06N5/04 , G06F16/955 , G06N20/00 , H04W4/029 , H04W4/21
摘要： A user's context history is analyzed to build a personality model describing the user's personality and interests. The personality model includes a plurality of metrics indicating the user's position on a plurality of personality dimensions, such as desire for novelty, tendency for extravagance, willingness to travel, love of the outdoors, preference for physical activity, and desire for solitude. A customized recommendation agent is then built based on the personality model, which selects a recommendation from a corpus to present to the user based on an affinity between the user's personality and the selected recommendation.
摘要翻译： 分析用户的上下文历史，构建描述用户个性和兴趣的个性模型。 个性模型包括指示用户在多个个性维度上的位置的多个度量，诸如欲望的新颖性，奢侈的倾向，旅行意愿，对户外的爱，体育活动的偏爱以及对孤独的渴望。 然后，基于人格模型构建定制推荐代理，该个性模型基于用户的个性与所选择的推荐之间的亲和度，从语料库中选择推荐给用户。
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5.发明申请公开(公告)号：US20140032208A1
公开(公告)日：2014-01-30
申请号：US13950169
申请日：2013-07-24
申请人： ARO, Inc.
IPC分类号： G06F17/27
CPC分类号： G06N5/04 , G06F17/2785 , G06F17/30876 , G06N5/02 , G06N99/005 , G06Q30/0631 , H04W4/02 , H04W4/21
摘要： Embodiments create and label context slices from observation data that together define a storyline of a user's movements. A context is a (possibly partial) specification of what a user was doing in the dimensions of time, place, and activity. Contexts can vary in their specificity, their semantic content, and their likelihood. A storyline is composed of a time-ordered sequence of contexts that partition a given span of time. A storyline is created through a process of data collection, slicing and labeling. Raw context data can be collected from a variety of observation sources with various error characteristics. Slicing refines the chaotic collection of contexts produced by data collection into a single consistent storyline composed of a sequence of contexts representing homogeneous time intervals. Labeling adds more specific and semantically meaningful data (e.g., geography, venue, activity) to the storyline produced by slicing.
摘要翻译： 实施例创建和标注来自观察数据的上下文切片，其一起界定用户运动的故事情节。 上下文是用户在时间，地点和活动的维度上所做的（可能是部分的）规范。 语境可能会因特异性，语义内容和可能性而异。 故事情节由分配给定时间段的时间序列的上下文组成。 通过数据收集，切片和标签的过程创建故事情节。 原始上下文数据可以从具有各种错误特征的各种观察源收集。 切片将由数据收集产生的上下文的混乱集合精炼成由表示均匀时间间隔的上下文序列组成的单一一致故事情节。 标签将更具体和语义上有意义的数据（例如，地理位置，场地，活动）添加到由切片产生的故事情节。
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公开(公告)号：US08892480B2
公开(公告)日：2014-11-18
申请号：US13950224
申请日：2013-07-24
申请人： ARO, Inc.
发明人： Kevin Francis Eustice , Alan Linchuan Liu , Michael Perkowitz , Andrew F. Hickl , Paul G. Allen
CPC分类号： G06N5/04 , G06F17/2785 , G06F17/30876 , G06N5/02 , G06N99/005 , G06Q30/0631 , H04W4/02 , H04W4/21
摘要： A user's context history is used to help select contextual information to provide to the user. Context data describing the user's current context is received and a plurality of information items corresponding to the user's current context are identified from a contextual information corpus. A personalized user behavior model for the user is applied to determine the likelihood that each of the identified information items will be of value to the user. One or more of the information items are selected based on the corresponding likelihoods and the selected information items are provided for presentation to the user.
摘要翻译： 用户的上下文历史用于帮助选择提供给用户的上下文信息。 接收描述用户当前上下文的上下文数据，并从上下文信息语料库中识别与用户当前上下文相对应的多个信息项。 应用用于用户的个性化用户行为模型来确定每个所识别的信息项对用户来说是有价值的可能性。 基于相应的可能性来选择信息项中的一个或多个，并且提供所选择的信息项以呈现给用户。
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7.发明授权公开(公告)号：US08838436B2
公开(公告)日：2014-09-16
申请号：US13950169
申请日：2013-07-24
申请人： ARO, Inc.
CPC分类号： G06N5/04 , G06F17/2785 , G06F17/30876 , G06N5/02 , G06N99/005 , G06Q30/0631 , H04W4/02 , H04W4/21
摘要： Embodiments create and label context slices from observation data that together define a storyline of a user's movements. A context is a (possibly partial) specification of what a user was doing in the dimensions of time, place, and activity. Contexts can vary in their specificity, their semantic content, and their likelihood. A storyline is composed of a time-ordered sequence of contexts that partition a given span of time. A storyline is created through a process of data collection, slicing and labeling. Raw context data can be collected from a variety of observation sources with various error characteristics. Slicing refines the chaotic collection of contexts produced by data collection into a single consistent storyline composed of a sequence of contexts representing homogeneous time intervals. Labeling adds more specific and semantically meaningful data (e.g., geography, venue, activity) to the storyline produced by slicing.
摘要翻译： 实施例创建和标注来自观察数据的上下文切片，其一起界定用户运动的故事情节。 上下文是用户在时间，地点和活动的维度上所做的（可能是部分的）规范。 语境可能会因特异性，语义内容和可能性而异。 故事情节由分配给定时间段的时间序列的上下文组成。 通过数据收集，切片和标签的过程创建故事情节。 原始上下文数据可以从具有各种错误特征的各种观察源收集。 切片将由数据收集产生的上下文的混乱集合精炼成由表示均匀时间间隔的上下文序列组成的单一一致故事情节。 标签将更具体和语义上有意义的数据（例如，地理位置，场地，活动）添加到由切片产生的故事情节。
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公开(公告)号：US20140032358A1
公开(公告)日：2014-01-30
申请号：US13950177
申请日：2013-07-24
申请人： ARO, Inc.
IPC分类号： G06Q30/06
CPC分类号： G06N5/04 , G06F16/955 , G06N20/00 , H04W4/029 , H04W4/21
摘要： A customized recommendation agent for the user is built using a behavioral model. The customized recommendation agent selects recommendations from a corpus to present to the user, based on the behavioral model and the user's current or predicted future context. The customized recommendation agent can be shared by the user with others, thus allowing others to access recommendations that may appeal to the user, for example, for use in planning joint activities. Because the user's recommendation agent is independent from the user's actual history, preferences can be shared without revealing a user's specific behavior.
摘要翻译： 使用行为模型构建用户的定制推荐代理。 定制推荐代理根据行为模型和用户当前或预测的未来背景，从语料库中选择推荐给用户呈现给用户。 定制的推荐代理可以由用户与他人共享，从而允许其他人访问可能吸引用户的建议，例如用于规划联合活动。 由于用户的推荐代理独立于用户的实际历史，所以可以共享偏好，而不会泄露用户的具体行为。
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