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1. 发明申请

US20140074524A1 Method and System for Business Outcome-Based Personalized Ranking of Information Objects 审中-公开
标题翻译：基于业务成果的信息对象个性化排名方法与系统
公开(公告)号：US20140074524A1
公开(公告)日：2014-03-13
申请号：US13608021
申请日：2012-09-10
申请人： Jeffrey S. Boston , Tina Groves , Jennifer Lai , Jie Lu , Shimei Pan , Mercan Topkara , Zhen Wen , Stephen P. Wood
发明人： Jeffrey S. Boston , Tina Groves , Jennifer Lai , Jie Lu , Shimei Pan , Mercan Topkara , Zhen Wen , Stephen P. Wood
IPC分类号： G06Q10/06
CPC分类号： G06Q10/063 , G06Q50/01
摘要： Business outcome-based personalized ranking of information objects is provided. Information objects in outcome-based business processes are ranked by recording information objects generated during a creation of the outcome-based business processes. At least one business process comprises an outcome attribute, and at least one business process comprises in-process information objects. A composite graph is generated of the information objects and business processes. Each node in the graph corresponds to an information object or a business process. Links between two information object nodes have a strength based on a content similarity and a social network distance. The in-process information object node connects to a corresponding business process node, and two business process nodes have a link if they are indicated as related in the business process information system. The information objects are ranked based on the link strengths.
摘要翻译：提供了基于业务成果的信息对象个性化排序。基于结果的业务流程中的信息对象通过记录在创建基于结果的业务流程期间生成的信息对象进行排名。至少一个业务流程包括结果属性，并且至少一个业务流程包括进程内信息对象。生成信息对象和业务流程的复合图。图中的每个节点对应于信息对象或业务流程。两个信息对象节点之间的链接具有基于内容相似性和社交网络距离的强度。进程内信息对象节点连接到相应的业务流程节点，并且如果业务流程信息系统中的相关业务流程节点被指示为两个，那么两个业务流程节点具有链路。信息对象基于链接强度进行排名。

2. 发明授权

US08914452B2 Automatically generating a personalized digest of meetings 有权
标题翻译：自动生成会议的个性化摘要
公开(公告)号：US08914452B2
公开(公告)日：2014-12-16
申请号：US13485415
申请日：2012-05-31
申请人： Jeffrey S. Boston , Jennifer C. Lai , Shimei Pan , Mercan Topkara , Stephen P. Wood
发明人： Jeffrey S. Boston , Jennifer C. Lai , Shimei Pan , Mercan Topkara , Stephen P. Wood
IPC分类号： G06F15/16
CPC分类号： G06K9/00751 , G06F17/278 , G06F17/30719 , G06Q10/10
摘要： Automatically generating a meeting digest of a set of meetings is provided. A set of topics of interest to the parties to the set of meetings is detected utilizing a user model associated with a user that is based on at least one of communications, relationships, and roles of the parties to the set of meetings. Topic-related content associated with the set of topics of interest to the parties is extracted from meeting data corresponding to the set of meetings. Then, the meeting digest of the set of meetings is generated using the topic-related content associated with the set of topics of interest to the parties extracted from the meeting data corresponding to the set of meetings.
摘要翻译：提供自动生成一组会议的会议摘要。使用与用户相关联的用户模型来检测该组会议的各方感兴趣的一组主题，该用户模型基于该组会议的各方的通信，关系和角色中的至少一个。与与该组会议相对应的会议数据中提取与各方感兴趣的主题相关联的主题相关内容。然后，使用与会议数据相对应的会议数据提取的与各方感兴趣的主题相关联的主题相关内容，生成会议摘要。

3. 发明申请

US20130325972A1 AUTOMATICALLY GENERATING A PERSONALIZED DIGEST OF MEETINGS 有权
标题翻译：自动生成个性化会议的最佳会议
公开(公告)号：US20130325972A1
公开(公告)日：2013-12-05
申请号：US13485415
申请日：2012-05-31
申请人： Jeffrey S. Boston , Jennifer C. Lai , Shimei Pan , Mercan Topkara , Stephen P. Wood
发明人： Jeffrey S. Boston , Jennifer C. Lai , Shimei Pan , Mercan Topkara , Stephen P. Wood
IPC分类号： G06F15/16
CPC分类号： G06K9/00751 , G06F17/278 , G06F17/30719 , G06Q10/10
摘要： Automatically generating a meeting digest of a set of meetings is provided. A set of topics of interest to the parties to the set of meetings is detected utilizing a user model associated with a user that is based on at least one of communications, relationships, and roles of the parties to the set of meetings. Topic-related content associated with the set of topics of interest to the parties is extracted from meeting data corresponding to the set of meetings. Then, the meeting digest of the set of meetings is generated using the topic-related content associated with the set of topics of interest to the parties extracted from the meeting data corresponding to the set of meetings.
摘要翻译：提供自动生成一组会议的会议摘要。使用与用户相关联的用户模型来检测该组会议的各方感兴趣的一组主题，该用户模型基于该组会议的各方的通信，关系和角色中的至少一个。与与该组会议相对应的会议数据中提取与各方感兴趣的主题相关联的主题相关内容。然后，使用与会议数据相对应的会议数据提取的与各方感兴趣的主题相关联的主题相关内容，生成会议摘要。

4. 发明申请

US20120209871A1 Automated Contextual Information Retrieval Based on Multi-Tiered User Modeling and Dynamic Retrieval Strategy 有权
标题翻译：基于多层次用户建模和动态检索策略的自动上下文信息检索
公开(公告)号：US20120209871A1
公开(公告)日：2012-08-16
申请号：US13024467
申请日：2011-02-10
申请人： Jennifer Lai , Jie Lu , Shimei Pan , Zhen Wen
发明人： Jennifer Lai , Jie Lu , Shimei Pan , Zhen Wen
IPC分类号： G06F17/30
CPC分类号： G06F17/30997 , H04L51/02
摘要： Automated contextual information retrieval techniques are provided based on multi-tiered user modeling and a dynamic retrieval strategy. Content relevant to a current message is presented by initially obtaining a multi-tiered user model containing a multi-tiered representation of interactions of a first user with each contact, wherein the multi-tiered representation includes a plurality of topic models each corresponding to interactions between the first user and one contact. The topic models contain a set of topics, each containing topic keywords. Context information is extracted based on content of the current message, a sender and/or a recipient of the current message, and the multi-tiered user model. A retrieval strategy is determined based on the extracted context information. Contextual queries are generated to search the information repositories selected based on the determined retrieval strategy. Content relevant to the current message is presented based on search results from the selected information repositories.
摘要翻译：基于多层次用户建模和动态检索策略提供了自动上下文信息检索技术。通过最初获得包含第一用户与每个联系人的交互的多层次表示的多层次用户模型来呈现与当前消息相关的内容，其中所述多层表示包括多个主题模型，每个主题模型对应于第一个用户和一个联系人。主题模型包含一组主题，每个主题包含主题关键字。基于当前消息的内容，当前消息的发送者和/或接收者以及多层次用户模型来提取上下文信息。基于提取的上下文信息确定检索策略。生成上下文查询以搜索基于确定的检索策略选择的信息库。基于所选信息存储库的搜索结果显示与当前消息相关的内容。

5. 发明授权

US09633140B2 Automated contextual information retrieval based on multi-tiered user modeling and dynamic retrieval strategy 有权
公开(公告)号：US09633140B2
公开(公告)日：2017-04-25
申请号：US13024467
申请日：2011-02-10
申请人： Jennifer Lai , Jie Lu , Shimei Pan , Zhen Wen
发明人： Jennifer Lai , Jie Lu , Shimei Pan , Zhen Wen
IPC分类号： G06F7/00 , G06F17/30 , H04L12/58
CPC分类号： G06F17/30997 , H04L51/02
摘要： Automated contextual information retrieval techniques are provided based on multi-tiered user modeling and a dynamic retrieval strategy. Content relevant to a current message is presented by initially obtaining a multi-tiered user model containing a multi-tiered representation of interactions of a first user with each contact, wherein the multi-tiered representation includes a plurality of topic models each corresponding to interactions between the first user and one contact. The topic models contain a set of topics, each containing topic keywords. Context information is extracted based on content of the current message, a sender and/or a recipient of the current message, and the multi-tiered user model. A retrieval strategy is determined based on the extracted context information. Contextual queries are generated to search the information repositories selected based on the determined retrieval strategy. Content relevant to the current message is presented based on search results from the selected information repositories.

6. 发明授权

US09256862B2 Multi-tiered approach to E-mail prioritization 有权
标题翻译：多层次的电子邮件优先排序方法
公开(公告)号：US09256862B2
公开(公告)日：2016-02-09
申请号：US13528598
申请日：2012-06-20
申请人： Jennifer C. Lai , Jie Lu , Shimei Pan , Zhen Wen
发明人： Jennifer C. Lai , Jie Lu , Shimei Pan , Zhen Wen
IPC分类号： G06F15/18 , G06Q10/10
CPC分类号： G06Q10/107
摘要： A method of automating incoming message prioritization. The method including training a global classifier of a computer system using training data. Dynamically training a user-specific classifier of the computer system based on a plurality of feedback instances. Inferring a topic of the incoming message received by the computer system based on a topic-based user model. Computing a plurality of contextual features of the incoming message. Determining a priority classification strategy for assigning a priority level to the incoming message based on the computed contextual features of the incoming message and a weighted combination of the global classifier and the user specific classifier. Classifying the incoming message based on the priority classification strategy.
摘要翻译：一种自动传入消息优先级的方法。该方法包括使用训练数据训练计算机系统的全局分类器。基于多个反馈实例动态训练计算机系统的用户专用分类器。基于基于主题的用户模型推断计算机系统接收到的传入消息的主题。计算传入消息的多个上下文特征。确定用于基于输入消息的计算的上下文特征以及全局分类器和用户特定分类器的加权组合来为入局消息分配优先级的优先级分类策略。根据优先级分类策略对传入的消息进行分类。

7. 发明申请

US20130339276A1 MULTI-TIERED APPROACH TO E-MAIL PRIORITIZATION 审中-公开
标题翻译：电子邮件优先的多层次的方法
公开(公告)号：US20130339276A1
公开(公告)日：2013-12-19
申请号：US13528598
申请日：2012-06-20
申请人： Jennifer C. Lai , Jie Lu , Shimei Pan , Zhen Wen
发明人： Jennifer C. Lai , Jie Lu , Shimei Pan , Zhen Wen
IPC分类号： G06F15/18
CPC分类号： G06Q10/107
摘要： A method of automating incoming message prioritization. The method including training a global classifier of a computer system using training data. Dynamically training a user-specific classifier of the computer system based on a plurality of feedback instances. Inferring a topic of the incoming message received by the computer system based on a topic-based user model. Computing a plurality of contextual features of the incoming message. Determining a priority classification strategy for assigning a priority level to the incoming message based on the computed contextual features of the incoming message and a weighted combination of the global classifier and the user specific classifier. Classifying the incoming message based on the priority classification strategy.
摘要翻译：一种自动传入消息优先级的方法。该方法包括使用训练数据训练计算机系统的全局分类器。基于多个反馈实例动态训练计算机系统的用户专用分类器。基于基于主题的用户模型推断计算机系统接收到的传入消息的主题。计算传入消息的多个上下文特征。确定用于基于输入消息的计算的上下文特征以及全局分类器和用户特定分类器的加权组合来为入局消息分配优先级的优先级分类策略。根据优先级分类策略对传入的消息进行分类。

8. 发明申请

US20130212047A1 MULTI-TIERED APPROACH TO E-MAIL PRIORITIZATION 有权
标题翻译：电子邮件优先的多层次的方法
公开(公告)号：US20130212047A1
公开(公告)日：2013-08-15
申请号：US13525173
申请日：2012-06-15
申请人： Jennifer C. Lai , Jie Lu , Shimei Pan , Zhen Wen
发明人： Jennifer C. Lai , Jie Lu , Shimei Pan , Zhen Wen
IPC分类号： G06F15/18
CPC分类号： G06Q10/107 , G06N5/00
摘要： An apparatus for automating a prioritization of an incoming message, including a batch learning module that generates a global classifier based on training data that is input to the batch learning module. A feedback learning module that generates a user-specific classifier based on a plurality of feedback instances. A feature extraction module that receives the incoming message and a topic-based user model, infers a topic of the incoming message based on the topic-based user model, and computes a plurality of contextual features of the incoming message. A classification module that dynamically determines a priority classification strategy for assigning a priority level to the incoming message based on the plurality of contextual features of the incoming message and a weighted combination of the global classifier and the user-specific classifier, and classifies the incoming message based on the priority classification strategy.
摘要翻译：一种用于自动化进入消息的优先级的装置，包括基于输入到批量学习模块的训练数据生成全局分类器的批量学习模块。反馈学习模块，其基于多个反馈实例生成用户特定的分类器。一种特征提取模块，其接收所述传入消息和基于主题的用户模型，基于所述基于所述主题的用户模型推断所述传入消息的主题，并且计算所述传入消息的多个上下文特征。一种分类模块，其基于所述输入消息的所述多个上下文特征以及所述全局分类器和所述用户特定分类器的加权组合来动态地确定用于向所述传入消息分配优先级的优先级分类策略，并且对所述传入消息进行分类基于优先级分类策略。

9. 发明授权

US09152953B2 Multi-tiered approach to E-mail prioritization 有权
标题翻译：多层次的电子邮件优先排序方法
公开(公告)号：US09152953B2
公开(公告)日：2015-10-06
申请号：US13525173
申请日：2012-06-15
申请人： Jennifer C. Lai , Jie Lu , Shimei Pan , Zhen Wen
发明人： Jennifer C. Lai , Jie Lu , Shimei Pan , Zhen Wen
IPC分类号： G06F15/18 , G06Q10/10 , G06N5/00
CPC分类号： G06Q10/107 , G06N5/00
摘要： An apparatus for automating a prioritization of an incoming message, including a batch learning module that generates a global classifier based on training data that is input to the batch learning module. A feedback learning module that generates a user-specific classifier based on a plurality of feedback instances. A feature extraction module that receives the incoming message and a topic-based user model, infers a topic of the incoming message based on the topic-based user model, and computes a plurality of contextual features of the incoming message. A classification module that dynamically determines a priority classification strategy for assigning a priority level to the incoming message based on the plurality of contextual features of the incoming message and a weighted combination of the global classifier and the user-specific classifier, and classifies the incoming message based on the priority classification strategy.
摘要翻译：一种用于自动化进入消息的优先级的装置，包括基于输入到批量学习模块的训练数据生成全局分类器的批量学习模块。反馈学习模块，其基于多个反馈实例生成用户特定的分类器。一种特征提取模块，其接收所述传入消息和基于主题的用户模型，基于所述基于所述主题的用户模型推断所述传入消息的主题，并且计算所述传入消息的多个上下文特征。一种分类模块，其基于所述输入消息的所述多个上下文特征以及所述全局分类器和所述用户特定分类器的加权组合来动态地确定用于向所述传入消息分配优先级的优先级分类策略，并且对所述传入消息进行分类基于优先级分类策略。

10. 发明申请

US20060015324A1 Method and apparatus for natural language generation 有权
标题翻译：自然语言生成的方法和装置
公开(公告)号：US20060015324A1
公开(公告)日：2006-01-19
申请号：US10890811
申请日：2004-07-14
申请人： Shimei Pan , James Shaw
发明人： Shimei Pan , James Shaw
IPC分类号： G06F17/27
CPC分类号： G06F17/2785 , G06F17/2881
摘要： One embodiment of the present method and apparatus for natural language generation enables a language generation system to generate a grammatically correct natural language sentence by retrieving and adapting one or more stored sentences having semantic features similar to semantic features of a system-generated semantic representation. The retrieval of stored sentences is guided at least in part by the ease with which the stored sentences may be adapted to produce a grammatically correct sentence, enabling rapid generation of accurate output.
摘要翻译：用于自然语言生成的本方法和装置的一个实施例使语言生成系统能够通过检索和调整具有与系统生成的语义表示的语义特征相似的语义特征的一个或多个存储的句子来生成语法上正确的自然语言句子。存储句子的检索至少部分地通过存储的句子可以被适应以便产生语法上正确的句子的方式来引导，从而能够快速产生准确的输出。

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