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1. 发明申请

US20080070209A1 IDENTIFYING INFLUENTIAL PERSONS IN A SOCIAL NETWORK 有权
标题翻译：在社会网络中识别受影响人
公开(公告)号：US20080070209A1
公开(公告)日：2008-03-20
申请号：US11533742
申请日：2006-09-20
申请人： Dong Zhuang , Benyu Zhang , Heng Zhang , Jeremy Tantrum , Teresa Mah , Hua-Jun Zeng , Zheng Chen , Jian Wang
发明人： Dong Zhuang , Benyu Zhang , Heng Zhang , Jeremy Tantrum , Teresa Mah , Hua-Jun Zeng , Zheng Chen , Jian Wang
IPC分类号： G09B19/00
CPC分类号： G06Q30/02 , G06Q10/10
摘要： An influential persons identification system and method for identifying a set of influential persons (or influencers) in a social network (such as an online social network). The influential persons set is generated such that by sending a message to the set the message will be propagated through the network at the greatest speed and coverage. A ranking of users is generated, and a pruning process is performed starting with the top-ranked user and working down the list. For each user on the list, the user is identified as an influencer and then the user and each of his friends are deleted from the social network users list. Next, the same process is performed for the second-ranked user, the third-ranked user, and so forth. The process terminates when the list of users of the social network is exhausted or the desired number of influencers on the influential person set is reached.
摘要翻译：在社交网络（如在线社交网络）中识别一组有影响力的人（或影响者）的有影响力的人员识别系统和方法。产生有影响力的人员，通过发送消息给消息集，消息将以最大的速度和覆盖率通过网络传播。生成用户排名，并从顶级用户开始执行修剪过程，并在列表中执行操作。对于列表中的每个用户，用户被识别为影响者，然后从社交网络用户列表中删除用户和他的每个朋友。接下来，对于第二等级的用户，第三等级的用户等执行相同的处理。当社交网络的用户列表用完或者达到期望数量的有影响力的人集合的影响者时，该过程终止。

2. 发明申请

US20120120086A1 Interactive and Scalable Treemap as a Visualization Service 审中-公开
标题翻译：交互式和可扩展的Treemap作为可视化服务
公开(公告)号：US20120120086A1
公开(公告)日：2012-05-17
申请号：US12947748
申请日：2010-11-16
申请人： Yingnong Dang , Dong Zhuang , He Huang , Haidong Zhang , Dongmei Zhang
发明人： Yingnong Dang , Dong Zhuang , He Huang , Haidong Zhang , Dongmei Zhang
IPC分类号： G09G5/02
CPC分类号： G06F16/904 , G09G2370/022 , G09G2370/027
摘要： Techniques for providing a visualization of an interactive and scalable treemap are described. A service provider hosts large-scale hierarchical data and supports online users who desire to visualize the large-scale hierarchical data in a treemap format on their computing devices.The user experience may be enhanced by providing a user interface for visualization of the interactive and scalable treemap. The visualization enables navigation and customization of data in the interactive and scalable treemap. The user experience is further enhanced by illustrating attributes are distinct by displaying a color or a pattern selected for a background or a bar of polygon. The user experience is further enhanced by providing the interactive and scalable treemap to the user on a website or on servers operated by a service or another third party service.
摘要翻译：描述了用于提供交互式和可缩放树状图的可视化的技术。服务提供商承载大型分层数据，并支持希望在其计算设备上以树形图格式显示大规模分层数据的在线用户。可以通过提供用于可视化交互式和可缩放树状图的用户界面来增强用户体验。可视化功能可以在交互式和可扩展的树形图中导航和定制数据。通过显示为背景或多边形条选择的颜色或图案来说明属性是不同的，进一步增强了用户体验。通过在网站或由服务或另一第三方服务器操作的服务器上向用户提供交互式和可缩放的树形图来进一步增强用户体验。

3. 发明授权

US08359276B2 Identifying influential persons in a social network 有权
标题翻译：识别社会网络中有影响力的人物
公开(公告)号：US08359276B2
公开(公告)日：2013-01-22
申请号：US11533742
申请日：2006-09-20
申请人： Dong Zhuang , Benyu Zhang , Heng Zhang , Jeremy Tantrum , Teresa Mah , Hua-Jun Zeng , Zheng Chen , Jian Wang
发明人： Dong Zhuang , Benyu Zhang , Heng Zhang , Jeremy Tantrum , Teresa Mah , Hua-Jun Zeng , Zheng Chen , Jian Wang
IPC分类号： G06Q99/00
CPC分类号： G06Q30/02 , G06Q10/10
摘要： An influential persons identification system and method for identifying a set of influential persons (or influencers) in a social network (such as an online social network). The influential persons set is generated such that by sending a message to the set the message will be propagated through the network at the greatest speed and coverage. A ranking of users is generated, and a pruning process is performed starting with the top-ranked user and working down the list. For each user on the list, the user is identified as an influencer and then the user and each of his friends are deleted from the social network users list. Next, the same process is performed for the second-ranked user, the third-ranked user, and so forth. The process terminates when the list of users of the social network is exhausted or the desired number of influencers on the influential person set is reached.
摘要翻译：在社交网络（如在线社交网络）中识别一组有影响力的人（或影响者）的有影响力的人员识别系统和方法。产生有影响力的人员，通过发送消息给消息集，消息将以最大的速度和覆盖率通过网络传播。生成用户排名，并从顶级用户开始执行修剪过程，并在列表中执行操作。对于列表中的每个用户，用户被识别为影响者，然后从社交网络用户列表中删除用户和他的每个朋友。接下来，对于第二等级的用户，第三等级的用户等执行相同的处理。当社交网络的用户列表用完或者达到期望数量的有影响力的人集合的影响者时，该过程终止。

4. 发明申请

US20080126411A1 DEMOGRAPHIC PREDICTION USING A SOCIAL LINK NETWORK 审中-公开
标题翻译：使用社会链接网络进行人脸预测
公开(公告)号：US20080126411A1
公开(公告)日：2008-05-29
申请号：US11535160
申请日：2006-09-26
申请人： Dong Zhuang , Benyu Zhang , Heng Zhang , Jeremy Tantrum , Teresa B. Mah , Hua-Jun Zeng , Zheng Chen , Jian Wang
发明人： Dong Zhuang , Benyu Zhang , Heng Zhang , Jeremy Tantrum , Teresa B. Mah , Hua-Jun Zeng , Zheng Chen , Jian Wang
IPC分类号： G06F7/00
CPC分类号： G06Q30/02 , G06Q10/04
摘要： A system, method, computer-readable media, and related techniques are disclosed for predicting demographic information of a user. A social link network is created and a search request for demographic information related to a first user within the social link network is received. The requested demographic information based on the demographic information of other users connected to the first user within the social link network is provided.
摘要翻译：公开了一种用于预测用户的人口统计信息的系统，方法，计算机可读介质和相关技术。创建社交链接网络，并且接收与社交链路网络内的第一用户相关的针对人口统计信息的搜索请求。提供了基于在社交网络中连接到第一用户的其他用户的人口统计信息的请求的人口统计信息。

5. 发明申请

US20110077998A1 CATEGORIZING ONLINE USER BEHAVIOR DATA 审中-公开
标题翻译：分类在线用户行为数据
公开(公告)号：US20110077998A1
公开(公告)日：2011-03-31
申请号：US12568707
申请日：2009-09-29
申请人： Jun Yan , Ning Liu , Lei Ji , Dong Zhuang , Zheng Chen
发明人： Jun Yan , Ning Liu , Lei Ji , Dong Zhuang , Zheng Chen
IPC分类号： G06Q10/00 , G06Q30/00 , G06F17/30
CPC分类号： G06Q30/02
摘要： A method for categorizing online user behavior data, including creating a target set of users based on an advertiser query, identifying two or more users in the target set having one or more first similar behavior attributes using a Minhash algorithm; and modifying the target set according to the two or more identified users.
摘要翻译：一种用于对在线用户行为数据进行分类的方法，包括基于广告商查询创建目标用户集合，使用Minhash算法识别具有一个或多个第一相似行为属性的目标集合中的两个或多个用户; 以及根据所述两个或多个识别的用户修改所述目标集合。

6. 发明申请

US20080104225A1 VISUALIZATION APPLICATION FOR MINING OF SOCIAL NETWORKS 审中-公开
标题翻译：可视化社会网络采矿申请
公开(公告)号：US20080104225A1
公开(公告)日：2008-05-01
申请号：US11555279
申请日：2006-11-01
申请人： Heng Zhang , Benyu Zhang , Teresa Mah , Dong Zhuang , Jeremy Tantrum , Ying Li
发明人： Heng Zhang , Benyu Zhang , Teresa Mah , Dong Zhuang , Jeremy Tantrum , Ying Li
IPC分类号： G06F15/173 , G06F15/177
CPC分类号： H04L67/306 , G06Q50/01 , H04L67/36
摘要： A social network visualization and mining system that includes a visualization application for mining social networks of users in an online social network. This visualization can be used to mine the social network for additional information and intelligence. The social network is displaying in graphical form, such as a node-link graph, with a center node representing the social network of a user being examined, and secondary nodes represent the primary user's friends. Lines represent links between the primary user and his friends, while various visualization features such as line thickness, line color, and text size are used to easily identify the type of relationship between users. The system also includes a topics visualization module, which builds and displays a social network based on a certain topic or keyword that is entered by the application user. A demographic prediction module examines a user's social network to predict demographics of users.
摘要翻译：一种社交网络可视化和挖掘系统，其中包括在在线社交网络中挖掘用户社交网络的可视化应用程序。这种可视化可用于挖掘社交网络以获取更多信息和智能。社交网络以图形形式显示，例如节点链接图，中心节点表示正在检查的用户的社交网络，次要节点表示主要用户的朋友。线代表主要用户和他的朋友之间的链接，而各种可视化功能（如线条粗细，线条颜色和文字大小）用于轻松识别用户之间的关系类型。该系统还包括主题可视化模块，其基于由应用程序用户输入的某个主题或关键字构建和显示社交网络。人口统计预测模块检查用户的社交网络以预测用户的人口统计。

7. 发明授权

US07707129B2 Text classification by weighted proximal support vector machine based on positive and negative sample sizes and weights 有权
标题翻译：基于正，负样本大小和权重的加权近端支持向量机进行文本分类
公开(公告)号：US07707129B2
公开(公告)日：2010-04-27
申请号：US11384889
申请日：2006-03-20
申请人： Dong Zhuang , Benyu Zhang , Zheng Chen , Hua-Jun Zeng , Jian Wang
发明人： Dong Zhuang , Benyu Zhang , Zheng Chen , Hua-Jun Zeng , Jian Wang
IPC分类号： G06F15/18 , G06E1/00 , G06E3/00
CPC分类号： G06F17/30707 , G06K9/6269
摘要： Embodiments of the invention relate to improvements to the support vector machine (SVM) classification model. When text data is significantly unbalanced (i.e., positive and negative labeled data are in disproportion), the classification quality of standard SVM deteriorates. Embodiments of the invention are directed to a weighted proximal SVM (WPSVM) model that achieves substantially the same accuracy as the traditional SVM model while requiring significantly less computational time. A weighted proximal SVM (WPSVM) model in accordance with embodiments of the invention may include a weight for each training error and a method for estimating the weights, which automatically solves the unbalanced data problem. And, instead of solving the optimization problem via the KKT (Karush-Kuhn-Tucker) conditions and the Sherman-Morrison-Woodbury formula, embodiments of the invention use an iterative algorithm to solve an unconstrained optimization problem, which makes WPSVM suitable for classifying relatively high dimensional data.
摘要翻译：本发明的实施例涉及对支持向量机（SVM）分类模型的改进。当文本数据显着不平衡（即正负标签数据不成比例）时，标准SVM的分类质量恶化。本发明的实施例涉及一种加权近端SVM（WPSVM）模型，其实现与传统SVM模型基本相同的精度，同时需要显着更少的计算时间。根据本发明的实施例的加权近端SVM（WPSVM）模型可以包括每个训练误差的权重和用于估计权重的方法，其自动地解决不平衡数据问题。而且，不是通过KKT（Karush-Kuhn-Tucker）条件和Sherman-Morrison-Woodbury公式来解决优化问题，而是本发明的实施例使用迭代算法来解决无约束优化问题，这使得WPSVM适合于相对分类高维数据。

8. 发明申请

US20070239638A1 Text classification by weighted proximal support vector machine 有权
标题翻译：通过加权近端支持向量机进行文本分类
公开(公告)号：US20070239638A1
公开(公告)日：2007-10-11
申请号：US11384889
申请日：2006-03-20
申请人： Dong Zhuang , Benyu Zhang , Zheng Chen , Hua-Jun Zeng , Jian Wang
发明人： Dong Zhuang , Benyu Zhang , Zheng Chen , Hua-Jun Zeng , Jian Wang
IPC分类号： G06F15/18
CPC分类号： G06F17/30707 , G06K9/6269
摘要： Embodiments of the invention relate to improvements to the support vector machine (SVM) classification model. When text data is significantly unbalanced (i.e., positive and negative labeled data are in disproportion), the classification quality of standard SVM deteriorates. Embodiments of the invention are directed to a weighted proximal SVM (WPSVM) model that achieves substantially the same accuracy as the traditional SVM model while requiring significantly less computational time. A weighted proximal SVM (WPSVM) model in accordance with embodiments of the invention may include a weight for each training error and a method for estimating the weights, which automatically solves the unbalanced data problem. And, instead of solving the optimization problem via the KKT (Karush-Kuhn-Tucker) conditions and the Sherman-Morrison-Woodbury formula, embodiments of the invention use an iterative algorithm to solve an unconstrained optimization problem, which makes WPSVM suitable for classifying relatively high dimensional data.
摘要翻译：本发明的实施例涉及对支持向量机（SVM）分类模型的改进。当文本数据显着不平衡（即正负标签数据不成比例）时，标准SVM的分类质量恶化。本发明的实施例涉及一种加权近端SVM（WPSVM）模型，其实现与传统SVM模型基本相同的精度，同时需要显着更少的计算时间。根据本发明的实施例的加权近端SVM（WPSVM）模型可以包括每个训练误差的权重以及用于估计权重的方法，其自动地解决不平衡数据问题。而且，不是通过KKT（Karush-Kuhn-Tucker）条件和Sherman-Morrison-Woodbury公式来解决优化问题，而是本发明的实施例使用迭代算法来解决无约束优化问题，这使得WPSVM适合于相对分类高维数据。

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