专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

1. 发明授权

US08190512B1 Computer-implemented clustering systems and methods for action determination 有权
标题翻译：计算机实现的集群系统和行动确定方法
公开(公告)号：US08190512B1
公开(公告)日：2012-05-29
申请号：US11851016
申请日：2007-09-06
申请人： Revathi Subramanian , Vijay S. Desai , Lizhong Wu
发明人： Revathi Subramanian , Vijay S. Desai , Lizhong Wu
IPC分类号： G06Q40/00
CPC分类号： G06Q10/10 , G06Q40/00 , G06Q40/025
摘要： Computer-implemented systems and methods for determining one or more actions to be taken with respect to a first entity. A computer-implemented method can be configured to receive data that is related to characteristics of the first entity as well as data that is related to a plurality of segments. Assignments are determined between the first entity and the segments based upon the characteristics of the first entity and the characteristics associated with the segments. A determined assignment includes a membership probability that is indicative of how probable is membership of the first entity with respect to a segment. One or more actions are determined for the first entity based upon the membership probabilities and action information associated with the assigned segments.
摘要翻译：用于确定关于第一实体要采取的一个或多个动作的计算机实现的系统和方法。计算机实现的方法可以被配置为接收与第一实体的特性相关的数据以及与多个段相关的数据。基于第一实体的特征和与段相关联的特征，在第一实体和段之间确定分配。确定的分配包括表示第一实体相对于段的可能性的可能性的成员概率。基于与分配的片段相关联的成员概率和动作信息，为第一实体确定一个或多个动作。

2. 发明授权

US08805737B1 Computer-implemented multiple entity dynamic summarization systems and methods 有权
标题翻译：计算机实现的多实体动态汇总系统和方法
公开(公告)号：US08805737B1
公开(公告)日：2014-08-12
申请号：US12938361
申请日：2010-11-02
申请人： Kevin Chaowen Chen , Vijay S. Desai , William Szczuka , Andrew Engel , Ho Ming Luk , Brian Lee Duke , Daniel J. Dotson , Revathi Subramanian , Paul Charles Dulany
发明人： Kevin Chaowen Chen , Vijay S. Desai , William Szczuka , Andrew Engel , Ho Ming Luk , Brian Lee Duke , Daniel J. Dotson , Revathi Subramanian , Paul Charles Dulany
IPC分类号： G06Q40/00 , G06Q20/40 , G06Q40/02
CPC分类号： G06Q40/00 , G06Q40/02
摘要： Systems and methods are provided for operation upon data processing devices are provided for operating with a fraud detection system. As an example, a system and method can be configured for receiving, throughout a current day in real-time or near real-time, financial transaction data representative of financial transactions initiated by different entities. At multiple times throughout the day, a summarization of the financial transaction data (which has been received within a time period within the current day) is generated. The generated summarization is used to determine whether fraud has occurred with respect to a financial transaction contained in the received authorization data or with respect to a subsequently occurring financial transaction.
摘要翻译：提供的系统和方法用于在提供用于与欺诈检测系统一起操作的数据处理设备上的操作。作为示例，可以配置系统和方法，用于在实时或接近实时的当前一天接收代表由不同实体发起的金融交易的金融交易数据。在一天的多次中，生成了金融交易数据（在当天内的一段时间内收到）的总结。所产生的摘要用于确定在接收到的授权数据中包含的金融交易或相对于随后发生的金融交易是否发生欺诈。

3. 发明授权

US08346691B1 Computer-implemented semi-supervised learning systems and methods 有权
标题翻译：计算机实施的半监督学习系统和方法
公开(公告)号：US08346691B1
公开(公告)日：2013-01-01
申请号：US11850861
申请日：2007-09-06
申请人： Revathi Subramanian , Vijay S. Desai , Hongrui Gong
发明人： Revathi Subramanian , Vijay S. Desai , Hongrui Gong
IPC分类号： G06F15/18
CPC分类号： G06N3/08
摘要： Computer-implemented systems and methods for determining a subset of unknown targets to investigate. For example, a method can be configured to receive a target data set, wherein the target data set includes known targets and unknown targets. A supervised model such as a neural network model is generated using the known targets. The unknown targets are used with the neural network model to generate values for the unknown targets. Analysis with an unsupervised model is performed using the target data set in order to determine which of the unknown targets are outliers. A comparison of list of outlier unknown targets is performed with the values for the unknown targets that were generated by the neural network model. The subset of unknown targets to investigate is determined based upon the comparison.
摘要翻译：用于确定未知目标子集的计算机实现的系统和方法进行调查。例如，可以将方法配置为接收目标数据集，其中目标数据集包括已知目标和未知目标。使用已知目标产生诸如神经网络模型的监督模型。未知目标与神经网络模型一起使用以生成未知目标的值。使用目标数据集执行使用无监督模型的分析，以确定哪些未知目标是异常值。使用由神经网络模型生成的未知目标的值来执行异常值未知目标列表的比较。基于比较确定未知目标的子集。

4. 发明申请

US20120317027A1 Computer-Implemented Systems And Methods For Real-Time Scoring Of Enterprise Data 审中-公开
标题翻译：计算机实现的系统和方法用于企业数据的实时评分
公开(公告)号：US20120317027A1
公开(公告)日：2012-12-13
申请号：US13158999
申请日：2011-06-13
申请人： Ho Ming Luk , Daniel J. Dotson , Paul C. Dulany , Revathi Subramanian , Brian Lee Duke , Vijay S. Desai
发明人： Ho Ming Luk , Daniel J. Dotson , Paul C. Dulany , Revathi Subramanian , Brian Lee Duke , Vijay S. Desai
IPC分类号： G06Q40/00 , G06F15/18 , G06N5/02
CPC分类号： G06Q40/02
摘要： Systems and methods are provided for providing real-time scoring of received transaction data. Transaction data describing a particular transaction that has occurred is received. The transaction data is stored in an enterprise database, where the enterprise database is configured to store transactions of disparate types, where the transaction data is stored using a plurality of segments, where a segment is formatted according to a template, and where the template is selected based on an attribute of the transaction, wherein the attribute is a customer attribute, an activity attribute, or a channel attribute. A transaction type of the particular transaction is determined. One or more models are selected from a pool of models based on the transaction type, wherein the one or more models are configured based on a plurality of records from the enterprise database, and a score of the received transaction data is generated based on the transaction data.
摘要翻译：提供系统和方法来提供接收到的交易数据的实时评分。接收到描述发生的特定事务的事务数据。交易数据存储在企业数据库中，其中企业数据库被配置为存储不同类型的事务，其中使用多个段来存储交易数据，其中根据模板格式化段，并且模板是基于事务的属性选择，其中该属性是客户属性，活动属性或信道属性。确定特定交易的交易类型。基于事务类型从模型池中选择一个或多个模型，其中基于来自企业数据库的多个记录配置一个或多个模型，并且基于该事务生成所接收的交易数据的得分数据。

5. 发明授权

US08015133B1 Computer-implemented modeling systems and methods for analyzing and predicting computer network intrusions 有权
标题翻译：计算机实现的建模系统和分析预测计算机网络入侵的方法
公开(公告)号：US08015133B1
公开(公告)日：2011-09-06
申请号：US11850842
申请日：2007-09-06
申请人： Lizhong Wu , Terrance Gordon Barker , Vijay S. Desai
发明人： Lizhong Wu , Terrance Gordon Barker , Vijay S. Desai
IPC分类号： G06N3/02
CPC分类号： H04L63/1416 , H04L63/1425
摘要： Computer-implemented systems and methods for analyzing activities associated with accesses of a computer network. A computer-implemented method can be configured to receive data related to the activities associated with the accesses of a computer network. The network activities data are segmented into a plurality of network activities segments. For each of the network activities segments, an anomaly detection predictive model is generated. The generated predictive models are for use in analyzing the activities associated with the computer network.
摘要翻译：用于分析与计算机网络的访问相关联的活动的计算机实现的系统和方法。计算机实现的方法可以被配置为接收与与计算机网络的访问相关联的活动相关的数据。网络活动数据被分割成多个网络活动段。对于每个网络活动段，生成异常检测预测模型。生成的预测模型用于分析与计算机网络相关的活动。

6. 发明申请

US20130103617A1 Computer-Implemented Systems And Methods For Forecasting And Estimation Using Grid Regression 有权
标题翻译：计算机实现的系统和使用网格回归的预测和估计方法
公开(公告)号：US20130103617A1
公开(公告)日：2013-04-25
申请号：US13278972
申请日：2011-10-21
申请人： Vijay S. Desai
发明人： Vijay S. Desai
IPC分类号： G06F15/18
CPC分类号： G06N99/005 , G06N3/08
摘要： Systems and methods are provided for estimating a value for a target variable. A plurality of known entities are assigned to cells of a grid, where the known entities are assigned to the cells based upon attribute data. A determination is made as to whether each cell has at least a threshold number of assigned known entities. When one of the cells contains fewer than the threshold number of known entities, cells are combined to form a super cell. A model is generated for each cell and super cell based upon target variable values for known entities assigned to that cell or super cell. Data for a target entity is received, and the target entity is assigned to one the cells. One of the models is selected based upon the cell assignment, and an estimate is generated for the target variable for the target entity using the selected model.
摘要翻译：提供了系统和方法来估计目标变量的值。多个已知实体被分配给网格的小区，其中已知实体基于属性数据被分配给小区。确定每个小区是否具有至少一个分配的已知实体的阈值数量。当其中一个单元包含少于已知实体的阈值数量时，将单元组合以形成超级单元。基于分配给该单元或超级单元的已知实体的目标变量值，为每个单元和超级单元生成模型。接收目标实体的数据，并将目标实体分配给一个小区。基于小区分配选择一个模型，并且使用所选择的模型为目标实体的目标变量生成估计。

7. 发明授权

US08768866B2 Computer-implemented systems and methods for forecasting and estimation using grid regression 有权
标题翻译：使用网格回归的计算机实现的预测和估计方法
公开(公告)号：US08768866B2
公开(公告)日：2014-07-01
申请号：US13278972
申请日：2011-10-21
申请人： Vijay S. Desai
发明人： Vijay S. Desai
IPC分类号： G06F15/18
CPC分类号： G06N99/005 , G06N3/08
摘要： Systems and methods are provided for estimating a value for a target variable. A plurality of known entities are assigned to cells of a grid, where the known entities are assigned to the cells based upon attribute data. A determination is made as to whether each cell has at least a threshold number of assigned known entities. When one of the cells contains fewer than the threshold number of known entities, cells are combined to form a super cell. A model is generated for each cell and super cell based upon target variable values for known entities assigned to that cell or super cell. Data for a target entity is received, and the target entity is assigned to one the cells. One of the models is selected based upon the cell assignment, and an estimate is generated for the target variable for the target entity using the selected model.
摘要翻译：提供了系统和方法来估计目标变量的值。多个已知实体被分配给网格的小区，其中已知实体基于属性数据被分配给小区。确定每个小区是否具有至少一个分配的已知实体的阈值数量。当其中一个单元包含少于已知实体的阈值数量时，将单元组合以形成超级单元。基于分配给该单元或超级单元的已知实体的目标变量值，为每个单元和超级单元生成模型。接收目标实体的数据，并将目标实体分配给一个小区。基于小区分配选择一个模型，并且使用所选择的模型为目标实体的目标变量生成估计。

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式