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1.发明申请公开(公告)号：US20160283858A1
公开(公告)日：2016-09-29
申请号：US14667415
申请日：2015-03-24
发明人： Ching-Yung Lin , Zhen Wen , Yale Song
CPC分类号： G06N20/00 , G06F16/374 , G06K9/00315 , G06K9/00375 , G06K9/46 , G06K9/6289 , G06K9/629 , G06N5/003
摘要： Techniques for multimodal data fusion having a multimodal hierarchical dictionary learning framework that learns latent subspaces with hierarchical overlaps are provided. In one aspect, a method for multi-view data fusion with hierarchical multi-view dictionary learning is provided which includes the steps of: extracting multi-view features from input data; defining feature groups that group together the multi-view features that are related; defining a hierarchical structure of the feature groups; and learning a dictionary using the feature groups and the hierarchy of the feature groups. A system for multi-view data fusion with hierarchical multi-view dictionary learning is also provided.
摘要翻译： 提供了一种多模态数据融合技术，具有使用层次重叠学习潜在子空间的多模态分层词典学习框架。 一方面，提供了一种具有分级多视角字典学习的多视点数据融合方法，包括以下步骤：从输入数据中提取多视点特征; 定义要组合相关的多视图功能的特征组; 定义特征组的分层结构; 并使用特征组和特征组的层次结构学习字典。 还提供了一种具有分层多视角字典学习的多视图数据融合系统。
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公开(公告)号：US09727821B2
公开(公告)日：2017-08-08
申请号：US13969151
申请日：2013-08-16
发明人： Ching-Yung Lin , Yale Song , Zhen Wen
CPC分类号： G06N7/005 , G06N5/022 , G06N99/005
摘要： A dataset including at least one temporal event sequence is collected. A one-class sequence classifier f(x) that obtains a decision boundary is statistically learned. At least one new temporal event sequence is evaluated, wherein the at least one new temporal event sequence is outside of the dataset. It is determined whether the at least one new temporal event sequence is one of a normal sequence or an abnormal sequence based on the evaluation. Numerous additional aspects are disclosed.
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3.发明申请公开(公告)号：US20160162792A1
公开(公告)日：2016-06-09
申请号：US15019595
申请日：2016-02-09
发明人： Jie Lu , Jeffrey S. Boston , Anni R. Coden , Jennifer Lai , Shimei Pan , Mercan Topkara , Zhen Wen , Stephen P. Wood
IPC分类号： G06N5/04
摘要： A system includes a user model module that generates a plurality of topic-specific user knowledge models for each user of a plurality of users, each topic-specific user knowledge model representing a level of knowledge possessed by a respective user on a single topic from a set of globally defined topics shared among the plurality of users, a expertise model building module that generates a plurality of topic-specific expert knowledge models, each topic-specific expert knowledge model representing an aggregate level of knowledge possessed by a plurality of expert users on a single topic from a set of globally defined topics shared among the plurality of users, and a processor of a computer that executes instructions for comparing the topic-specific user knowledge model of the first user with the topic-specific expert knowledge model for a respective topic to determine a distance between a user knowledge level and an aggregate expert knowledge level for the topic.
摘要翻译： 一种系统包括用户模型模块，用于为多个用户的每个用户生成多个专题用户知识模型，每个特定用户知识模型表示相应用户在单个主题上拥有的知识水平，来自 在多个用户之间共享的一组全球定义的主题，一个产生多个专题专家知识模型的专业知识模型构建模块，每个专题专家知识模型表示多个专家用户拥有的知识聚合级别 来自在多个用户之间共享的一组全球定义的主题的单个主题，以及执行用于将第一用户的主题特定用户知识模型与用于相应的主题专用知识模型进行比较的指令的计算机的处理器 主题来确定用户知识水平与主题的聚合专家知识水平之间的距离。
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4.发明授权公开(公告)号：US09275332B2
公开(公告)日：2016-03-01
申请号：US13648988
申请日：2012-10-10
发明人： Jie Lu , Jeffrey Scott Boston , Anni Rosa Coden , Jennifer Ceil Lai , Shimei Pan , Mercan Topkara , Zhen Wen , Stephen Peter Wood
摘要： A method including generating a global topic model based on a set of data that is updated according to an activity of each user of a plurality of users, the global topic model including a topic representation for a topic, generating a plurality of user models, each user model being generated based on the activity of a respective user, generating an expertise model for the topic based on the activity of at least one user of the plurality of users, the expertise model for the topic setting a target level of knowledge for a first user of the plurality of users, comparing a user model of the first user with the expertise model for the topic, the comparing being performed by a processor of a computer system, and recommending an activity associated with the set of data to the first user based on the comparison.
摘要翻译： 一种方法，包括基于根据多个用户的每个用户的活动而更新的数据集，生成全球主题模型，所述全局主题模型包括主题的主题表示，生成多个用户模型，每个 基于相应用户的活动生成用户模型，基于多个用户中的至少一个用户的活动，为该主题生成专业知识模型，该主题的专业知识模型为第一个用户设置知识的目标级别 所述多个用户的用户将所述第一用户的用户模型与所述主题的专业知识模型进行比较，所述比较由计算机系统的处理器执行，并且向所述第一用户推荐与所述数据集相关联的活动 比较。
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公开(公告)号：US20150095250A1
公开(公告)日：2015-04-02
申请号：US14042114
申请日：2013-09-30
发明人： Jennifer Lai , Jie Lu , Shimei Pan , Marcel C. Rosu , Zhen Wen
CPC分类号： G06Q10/105 , G06F16/337
摘要： A method of modeling a user includes performing a role-based classification of tangible interactions involving the user performed via a computer system of an organization, creating a collection of role-specific interactions, creating, from the collection of role-specific interactions, a plurality of role-specific models of the user, wherein the plurality of role-specific models constitute a user model of the user, outputting one or more of the role-specific models to a different user model associated with a different user, and consolidating the output one or more of the role-specific models with a second plurality of role-specific models of the different user model within the different user model.
摘要翻译： 对用户进行建模的方法包括执行涉及通过组织的计算机系统执行的用户的有形交互的基于角色的分类，创建角色特定交互的集合，从角色特定交互的集合中创建多个 其中所述多个角色特定模型构成所述用户的用户模型，将所述角色特定模型中的一个或多个输出到与不同用户相关联的不同用户模型，并且将所述输出 具有不同用户模型内的不同用户模型的第二多个角色特定模型的角色特定模型中的一个或多个。
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公开(公告)号：US11182683B2
公开(公告)日：2021-11-23
申请号：US15019464
申请日：2016-02-09
发明人： Jie Lu , Jeffrey S. Boston , Anni R. Coden , Jennifer Lai , Shimei Pan , Mercan Topkara , Zhen Wen , Stephen P. Wood
摘要： A method includes generating, as executed by a processor on a computer, a plurality of topic-specific user knowledge models for each user of a plurality of users, each topic-specific user knowledge model representing a level of knowledge possessed by a respective user on a single topic from a set of globally defined topics shared among the plurality of users, generating a plurality of topic-specific expert knowledge models, each topic-specific expert knowledge model representing an aggregate level of knowledge possessed by a plurality of expert users on a single topic from a set of globally defined topics shared among the plurality of users, comparing the topic-specific user knowledge model of the first user with the topic-specific expert knowledge model for a respective topic to determine a distance between a user knowledge level and an aggregate expert knowledge level for the topic.
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公开(公告)号：US10776710B2
公开(公告)日：2020-09-15
申请号：US14667415
申请日：2015-03-24
发明人： Ching-Yung Lin , Zhen Wen , Yale Song
摘要： Techniques for multimodal data fusion having a multimodal hierarchical dictionary learning framework that learns latent subspaces with hierarchical overlaps are provided. In one aspect, a method for multi-view data fusion with hierarchical multi-view dictionary learning is provided which includes the steps of: extracting multi-view features from input data; defining feature groups that group together the multi-view features that are related; defining a hierarchical structure of the feature groups; and learning a dictionary using the feature groups and the hierarchy of the feature groups. A system for multi-view data fusion with hierarchical multi-view dictionary learning is also provided.
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公开(公告)号：US09256670B2
公开(公告)日：2016-02-09
申请号：US14050514
申请日：2013-10-10
发明人： Nan Cao , Ching-Yung Lin , Fei Wang , Zhen Wen
CPC分类号： G06F17/30684 , G06F17/30696 , G06F17/30716 , G06F17/30867 , G06Q10/00 , H04L51/32
摘要： Visualizing social media conflict is provided. Textual messages by a set of human users connected via a network regarding a particular topic are collected. Active users in the set of human users authoring a number of textual messages regarding the particular topic more than a threshold number of textual messages are selected. Keywords are selected that occur more than a threshold number of times within the textual messages regarding the particular topic. A sentiment score is computed for each of the keywords occurring more than the threshold number of times within the textual messages using a keyword co-occurrence graph. A sentiment of each of the active users is determined based on the computed sentiment score of each of the selected keywords that are authored by a particular active user.
摘要翻译： 提供了可视化的社交媒体冲突。 收集通过网络连接的一组人类用户关于特定主题的文本消息。 选择一组人类用户中的有用用户，创建关于特定主题的多个文本消息超过阈值数量的文本消息。 选择在关于特定主题的文本消息内出现超过阈值次数的关键字。 使用关键字同现图来计算在文本消息内超过门限次数的每个关键字的情绪评分。 基于由特定活动用户创作的每个所选择的关键字的计算情绪评分来确定每个活动用户的情绪。
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公开(公告)号：US20150052090A1
公开(公告)日：2015-02-19
申请号：US13969151
申请日：2013-08-16
发明人： Ching-Yung Lin , Yale Song , Zhen Wen
CPC分类号： G06N7/005 , G06N5/022 , G06N99/005
摘要： A dataset including at least one temporal event sequence is collected. A one-class sequence classifier f(x) that obtains a decision boundary is statistically learned. At least one new temporal event sequence is evaluated, wherein the at least one new temporal event sequence is outside of the dataset. It is determined whether the at least one new temporal event sequence is one of a normal sequence or an abnormal sequence based on the evaluation. Numerous additional aspects are disclosed.
摘要翻译： 收集包括至少一个时间事件序列的数据集。 统计学得到一个获得决策边界的一类序列分类器f（x）。 评估至少一个新的时间事件序列，其中所述至少一个新的时间事件序列在数据集之外。 基于评估确定至少一个新的时间事件序列是正常序列还是异常序列之一。 公开了许多附加方面。
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公开(公告)号：US09779161B2
公开(公告)日：2017-10-03
申请号：US14994456
申请日：2016-01-13
发明人： Nan Cao , Ching-Yung Lin , Fei Wang , Zhen Wen
CPC分类号： G06F17/30684 , G06F17/30696 , G06F17/30716 , G06F17/30867 , G06Q10/00 , H04L51/32
摘要： Visualizing social media conflict is provided. Active users in a set of human users authoring a number of textual messages regarding a particular topic more than a threshold number of textual messages are selected. Keywords are selected that occur more than a threshold number of times within the textual messages regarding the particular topic. A sentiment score is computed for each of the keywords occurring more than the threshold number of times within the textual messages using a keyword co-occurrence graph. A sentiment of each of the active users is determined based on the computed sentiment score of each of the selected keywords that are authored by a particular active user. Two distinct groups from the active users are selected based on at least one of a relationship between the two distinct groups and a determined degree of conflict between the two distinct groups with regard to the particular topic.
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