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    Detecting fraudulent mobile money transactions
    1.
    发明授权
    Detecting fraudulent mobile money transactions 有权
    检测诈骗手机货币交易

    公开(公告)号：US08458090B1

    公开(公告)日：2013-06-04

    申请号：US13449545

    申请日：2012-04-18

    申请人： Vishal S. Batra ,  Dinesh Garg ,  Ravi Kothari ,  Raghuram Krishnapuram ,  Sumit Negi ,  Gyana R. Parija

    发明人： Vishal S. Batra ,  Dinesh Garg ,  Ravi Kothari ,  Raghuram Krishnapuram ,  Sumit Negi ,  Gyana R. Parija

    IPC分类号： G06Q40/00 ,  G06Q99/00

    CPC分类号： G06Q40/00 ,  G06Q99/00

    摘要： A method, an apparatus and an article of manufacture for detecting a fraudulent mobile money transaction. The method includes determining a reputation score for at least one customer based on historical data, determining multiple patterns related to fraudulent mobile money transaction activities by using the reputation score and the historical data, automatically detecting at least one of the patterns in mobile money transactions incoming from at least one other customer, and classifying the at least one detected pattern as a fraudulent mobile money transaction or a genuine mobile money transaction.

    摘要翻译： 一种用于检测欺诈性移动货币交易的方法，装置和制品。 该方法包括基于历史数据确定至少一个客户的信誉得分，通过使用信誉分数和历史数据确定与欺诈性移动货币交易活动相关的多种模式，自动检测流动货币交易中的至少一种模式 从至少一个其他客户，并将所述至少一个检测到的模式分类为欺诈性移动货币交易或真正的移动货币交易。

    OPTIMIZED CUSTOMER TARGETING BASED ON TEMPLATE CRM OFFERS
    4.
    发明申请
    OPTIMIZED CUSTOMER TARGETING BASED ON TEMPLATE CRM OFFERS 审中-公开
    基于模板CRM优化的优化客户定位

    公开(公告)号：US20120109664A1

    公开(公告)日：2012-05-03

    申请号：US12916665

    申请日：2010-11-01

    申请人： Raghuram Krishnapuram ,  Sumit Negi ,  Deepak S. Padmanabhan ,  Karthik Visweswariah

    发明人： Raghuram Krishnapuram ,  Sumit Negi ,  Deepak S. Padmanabhan ,  Karthik Visweswariah

    IPC分类号： G06Q30/00

    CPC分类号： G06Q30/02

    摘要： A Customer Relationship Management (CRM) offer template is established in data storage and includes at least one variable field and having at least one offer attribute. For each of a plurality of customer groups, a data processing system calculates an expected benefit to be obtained by sending an instantiated CRM offer to a customer based upon historical responses, offer cost, and legal values of the at least one variable field. The data processing system outputs a CRM offer instance and target list of customers that maximizes the expected benefit.

    摘要翻译： 在数据存储中建立客户关系管理（CRM）提供模板，并且包括至少一个变量字段并具有至少一个报价属性。 对于多个客户组中的每一个，数据处理系统基于历史响应，提供成本和至少一个可变字段的合法值，向客户发送实例化的CRM提供来计算要获得的预期收益。 数据处理系统输出一个客户关系管理提供实例和最大化预期收益的客户目标列表。

    System and method for extraction of factoids from textual repositories
    6.
    发明授权
    System and method for extraction of factoids from textual repositories 失效
    从文本库中提取事实的系统和方法

    公开(公告)号：US08706730B2

    公开(公告)日：2014-04-22

    申请号：US11321177

    申请日：2005-12-29

    申请人： Sachindra Joshi ,  Raghuram Krishnapuram ,  Nimit Kumar ,  Kiran Mehta ,  Sumit Negi ,  Ganesh Ramakrishnan ,  Scott R Holmes

    发明人： Sachindra Joshi ,  Raghuram Krishnapuram ,  Nimit Kumar ,  Kiran Mehta ,  Sumit Negi ,  Ganesh Ramakrishnan ,  Scott R Holmes

    IPC分类号： G06F17/30

    CPC分类号： G06F17/30864 ,  G06F17/30705

    摘要： A method (400) is disclosed of extracting factoids from text repositories, with the factoids being associated with a given factoid category. The method (400) starts by training a classifier (230) to recognize factoids relevant to that given factoid category. Documents or document summaries relevant to the given factoid category is next collected (410) from the text repositories. Sentences having a predetermined association to the given factoid category is extracted (420) from the documents or said document summaries. Those sentences are classified (440), in a noisy environment, using the classifier (230) to extract snippets containing phrases relevant to the given factoid category. It is the extracted snippets that are the factoid associated with the given factoid category.

    摘要翻译： 公开了一种从文本存储库中提取事实框架的方法（400），其中事实框架与给定的类别类别相关联。 方法（400）通过训练分类器（230）开始，以识别与该给定的类别类别相关的因子。 接下来从文本存储库收集与文件类型相关的文档或文档摘要（410）。 具有与给定类别类别的预定关联的句子从文档或所述文档摘要中提取（420）。 这些句子在嘈杂的环境中被分类（440），使用分类器（230）提取包含与给定类别类别相关的短语的片段。 提取的片段是与给定类实体类别相关联的实例。

    System and method for extraction of factoids from textual repositories
    8.
    发明申请
    System and method for extraction of factoids from textual repositories 失效
    从文本库中提取事实的系统和方法

    公开(公告)号：US20070162447A1

    公开(公告)日：2007-07-12

    申请号：US11321177

    申请日：2005-12-29

    申请人： Sachindra Joshi ,  Raghuram Krishnapuram ,  Nimit Kumar ,  Kiran Mehta ,  Sumit Negi ,  Ganesh Ramakrishnan ,  Scott Holmes

    发明人： Sachindra Joshi ,  Raghuram Krishnapuram ,  Nimit Kumar ,  Kiran Mehta ,  Sumit Negi ,  Ganesh Ramakrishnan ,  Scott Holmes

    IPC分类号： G06F7/00

    CPC分类号： G06F17/30864 ,  G06F17/30705

    摘要： A method (400) is disclosed of extracting factoids from text repositories, with the factoids being associated with a given factoid category. The method (400) starts by training a classifier (230) to recognise factoids relevant to that given factoid category. Documents or document summaries relevant to the given factoid category is next collected (410) from the text repositories. Sentences having a predetermined association to the given factoid category is extracted (420) from the documents or said document summaries. Those sentences are classified (440), in a noisy environment, using the classifier (230) to extract snippets containing phrases relevant to the given factoid category. It is the extracted snippets that are the factoid associated with the given factoid category.

    摘要翻译： 公开了一种从文本存储库中提取事实框架的方法（400），其中事实框架与给定的类别类别相关联。 方法（400）通过训练分类器（230）开始，以识别与该给定的类别类别相关的因子。 接下来从文本存储库收集与文件类型相关的文档或文档摘要（410）。 具有与给定类别类别的预定关联的句子从文档或所述文档摘要中提取（420）。 这些句子在嘈杂的环境中被分类（440），使用分类器（230）提取包含与给定类别类别相关的短语的片段。 提取的片段是与给定类实体类别相关联的实例。