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。

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。

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。

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。

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。

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.

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。

公开(公告)号：US20100205238A1

公开(公告)日：2010-08-12

申请号：US12367132

申请日：2009-02-06

申请人： Nan Cao ,  David H. Gotz ,  Peter Kissa ,  Shi Xia Liu ,  Jie Lu ,  Wei Hong Qian ,  Zhen Wen ,  Michelle Zhou

发明人： Nan Cao ,  David H. Gotz ,  Peter Kissa ,  Shi Xia Liu ,  Jie Lu ,  Wei Hong Qian ,  Zhen Wen ,  Michelle Zhou

IPC分类号： G06F15/16 ,  G06F17/30

CPC分类号： G06Q10/10 ,  G06Q10/06

摘要： Methods and apparatus are provided for intelligent exploratory visualization and analysis. A semantics-based client-server application architecture is provided that enables interactive visualization and analysis applications over the web. From the client perspective, user activities are observed and the client determines if a sequence of user activities comprises one or more predefined semantics-based user actions. Semantics-based action descriptor are then sent to the server, optionally with any related parameters, and a response is then received from the server. From the server perspective, one or more semantics-based action descriptors are received from the client with an action type selected from a predefined set of types, wherein the semantics-based action descriptors are based on a sequence of activities of a user. The server processes the semantics-based action descriptors and sends a response to the client in response to the one or more semantics-based action descriptors.

摘要翻译： 提供了智能探索可视化和分析的方法和设备。 提供了一种基于语义的客户机 - 服务器应用程序体系结构，可通过Web进行交互式可视化和分析应用程序。 从客户端的角度来看，观察用户活动，并且客户端确定用户活动的序列是否包含一个或多个预定义的基于语义的用户动作。 然后将基于语义的动作描述符发送到服务器，可选地具有任何相关参数，然后从服务器接收响应。 从服务器的角度来看，从客户端接收从预定义的一组类型中选择的动作类型的一个或多个基于语义的动作描述符，其中基于语义的动作描述符基于用户的一系列活动。 服务器处理基于语义的动作描述符，并响应于一个或多个基于语义的动作描述符向客户端发送响应。

公开(公告)号：US09009147B2

公开(公告)日：2015-04-14

申请号：US13213856

申请日：2011-08-19

申请人： Jingrui He ,  Ravi B. Konuru ,  Ching-Yung Lin ,  Hanghang Tong ,  Zhen Wen

发明人： Jingrui He ,  Ravi B. Konuru ,  Ching-Yung Lin ,  Hanghang Tong ,  Zhen Wen

IPC分类号： G06F17/30 ,  G06F7/00

CPC分类号： G06F17/3053 ,  G06F17/30592 ,  G06F17/30958 ,  G06F2216/03

摘要： A method, system and computer program product for finding a diversified ranking list for a given query. In one embodiment, a multitude of date items responsive to the query are identified, a marginal score is established for each data item; and a set, or ranking list, of the data items is formed based on these scores. This ranking list is formed by forming an initial set, and one or more data items are added to the ranking list based on the marginal scores of the data items. In one embodiment, each of the data items has a measured relevance and a measured diversity value, and the marginal scores for the data items are based on the measured relevance and the measured diversity values of the data items.

摘要翻译： 一种用于查找给定查询的多样化排名列表的方法，系统和计算机程序产品。 在一个实施例中，识别响应于查询的多个日期项目，为每个数据项目建立边际分数; 并且基于这些分数形成数据项的集合或排名列表。 该排序列表通过形成初始集合而形成，并且基于数据项目的边际分数将一个或多个数据项目添加到排名列表。 在一个实施例中，每个数据项具有测量的相关性和测量的分集值，并且数据项的边际分数基于所测量的相关性和所测量的数据项的分集值。

公开(公告)号：US07849138B2

公开(公告)日：2010-12-07

申请号：US12038386

申请日：2008-02-27

申请人： Xiaohui Gu ,  Zon-Yin Shae ,  Zhen Wen ,  Philip S. Yu

发明人： Xiaohui Gu ,  Zon-Yin Shae ,  Zhen Wen ,  Philip S. Yu

IPC分类号： G06F15/16 ,  H04L12/16

CPC分类号： H04L12/1818 ,  H04L45/16 ,  H04L45/48

摘要： A system and computer program product for establishing multi-party VoIP conference audio calls in a distributed, peer-to-peer network where any number of nodes are able to arbitrarily and asynchronously start or stop producing audio output to be mixed into a single composite audio stream that is distributed to all nodes. A single distribution tree is used that has optimal communications characteristics to distribute the composite audio signal to all nodes. An audio mixing tree is established and maintained by adaptively and dynamically adding and merging intermediate mixing nodes operating between user nodes and the root of the single distribution tree. The intermediate mixing nodes and the root of the single distribution tree are all hosted, in an exemplary embodiment, on user nodes that are endpoints of the distribution tree.

摘要翻译： 一种用于在分布式对等网络中建立多方VoIP会议音频呼叫的系统和计算机程序产品，其中任何数量的节点能够任意地和异步地开始或停止产生要混合到单个复合音频中的音频输出 分发给所有节点的流。 使用具有最佳通信特性以将复合音频信号分配给所有节点的单个分发树。 通过自适应地动态地添加和合并在用户节点和单个分发树的根之间运行的中间混合节点来建立和维护音频混合树。 在示例性实施例中，分发树的中间混合节点和根分别在作为分发树的端点的用户节点上托管。