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1. 发明申请

US20050159996A1 Predictive modeling of consumer financial behavior using supervised segmentation and nearest-neighbor matching 有权
标题翻译：使用监督分割和最近邻匹配的消费者财务行为的预测建模
公开(公告)号：US20050159996A1
公开(公告)日：2005-07-21
申请号：US11012812
申请日：2004-12-14
申请人： Michael Lazarus , Larry Peranich , Frederique Vernhes , Matthias Blume , Kenneth Brown , William Caid , Ted Dunning , Gerald Russell , Kevin Sitze
发明人： Michael Lazarus , Larry Peranich , Frederique Vernhes , Matthias Blume , Kenneth Brown , William Caid , Ted Dunning , Gerald Russell , Kevin Sitze
IPC分类号： G06Q30/02 , G06F17/60
CPC分类号： G06Q30/02 , G06Q30/0202 , G06Q30/0207 , G06Q30/0241 , G06Q30/0255 , G06Q30/0269 , G06Q30/0601
摘要： Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Supervised segmentation is applied to merchant vectors to form the merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments. The consumer profiles include consumer vectors derived as summary vectors of selected merchants patronized by the consumer. Predictions of consumer behavior are made by applying nearest-neighbor analysis to consumer vectors, thus facilitating the targeting of promotional offers to consumers most likely to respond positively.
摘要翻译：通过将消费者交易数据应用于与商家细分相关的预测模型，提供消费者财务行为的预测建模，包括对特定营销努力的可能响应的确定。商业细分是根据交易序列中商家的共同出现从消费者交易数据中得出的。商家向量表示特定商家，并且在向量空间中对齐，作为商家与预期频繁相同程度的函数。监督分割被应用于商家向量以形成商家分段。商业细分预测模型根据消费者以前的支出，为每个特定消费者的每个商业细分市场提供支出预测。消费者个人资料描述了每个消费者在商家细分中以及跨商家细分的消费的总体统计。消费者资料包括作为由消费者光顾的所选商家的汇总向量导出的消费者向量。消费者行为的预测是通过对消费者向量应用最近邻分析来做出的，从而有助于向最有可能积极响应的消费者定位促销优惠。

2. 发明申请

US20070244741A1 Predictive Modeling of Consumer Financial Behavior Using Supervised Segmentation and Nearest-Neighbor Matching 有权
标题翻译：使用监督分割和最近邻匹配的消费者金融行为的预测建模
公开(公告)号：US20070244741A1
公开(公告)日：2007-10-18
申请号：US11623266
申请日：2007-01-15
申请人： Matthias Blume , Michael Lazarus , Larry Peranich , Frederique Vernhes , Kenneth Brown , William Caid , Ted Dunning , Gerald Russell , Kevin Sitze
发明人： Matthias Blume , Michael Lazarus , Larry Peranich , Frederique Vernhes , Kenneth Brown , William Caid , Ted Dunning , Gerald Russell , Kevin Sitze
IPC分类号： G06F17/30
CPC分类号： G06Q30/02 , G06Q30/0202 , G06Q30/0207 , G06Q30/0241 , G06Q30/0255 , G06Q30/0269 , G06Q30/0601
摘要： Predictive modeling of consumer financial behavior, including determination of likely responses to particular marketing efforts, is provided by application of consumer transaction data to predictive models associated with merchant segments. The merchant segments are derived from the consumer transaction data based on co-occurrences of merchants in sequences of transactions. Merchant vectors represent specific merchants, and are aligned in a vector space as a function of the degree to which the merchants co-occur more or less frequently than expected. Supervised segmentation is applied to merchant vectors to form the merchant segments. Merchant segment predictive models provide predictions of spending in each merchant segment for any particular consumer, based on previous spending by the consumer. Consumer profiles describe summary statistics of each consumer's spending in the merchant segments, and across merchant segments. The consumer profiles include consumer vectors derived as summary vectors of selected merchants patronized by the consumer. Predictions of consumer behavior are made by applying nearest-neighbor analysis to consumer vectors, thus facilitating the targeting of promotional offers to consumers most likely to respond positively.
摘要翻译：通过将消费者交易数据应用于与商家细分相关的预测模型，提供消费者财务行为的预测建模，包括对特定营销努力的可能响应的确定。商业细分是根据交易序列中商家的共同出现从消费者交易数据中得出的。商家向量表示特定商家，并且在向量空间中对齐，作为商家与预期频繁相同程度的函数。监督分割被应用于商家向量以形成商家分段。商业细分预测模型根据消费者以前的支出，为每个特定消费者的每个商业细分市场提供支出预测。消费者个人资料描述了每个消费者在商家细分中以及跨商家细分的消费的总体统计。消费者资料包括作为由消费者光顾的所选商家的汇总向量导出的消费者向量。消费者行为的预测是通过对消费者向量应用最近邻分析来做出的，从而有助于向最有可能积极响应的消费者定位促销优惠。

3. 发明申请

US20120150779A1 Automated Entity Identification for Efficient Profiling in an Event Probability Prediction System 有权
标题翻译：事件概率预测系统中高效分析的自动实体识别
公开(公告)号：US20120150779A1
公开(公告)日：2012-06-14
申请号：US13399067
申请日：2012-02-17
申请人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
发明人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
IPC分类号： G06F15/18 , G06N7/00
CPC分类号： G06N5/02 , G06N99/005 , G06Q40/00
摘要： A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.
摘要翻译：一种用于自动化实体识别的计算机实现的方法和系统，用于事件概率预测系统中的有效分析。定义属于一个或多个实体类的实体的第一子集。基于实体的第一子集中的每个实体的事务行为的一组可能结果，为实体子集中的每个实体构建至少一个历史简档。基于历史简档，选择具有与交易相关联的交易行为的实体的第二子集，所述交易行为从所述一组可能结果中预测至少一个目标结果。实体的第一个子集与第二个实体子集重新定义。

4. 发明申请

US20090222243A1 Adaptive Analytics 审中-公开
标题翻译：自适应分析
公开(公告)号：US20090222243A1
公开(公告)日：2009-09-03
申请号：US12040796
申请日：2008-02-29
申请人： Scott M. Zoldi , Larry Peranich , Jehangir Athwal , Uwe Mayer , Sajama
发明人： Scott M. Zoldi , Larry Peranich , Jehangir Athwal , Uwe Mayer , Sajama
IPC分类号： G06F17/10
CPC分类号： G06Q10/04 , G06Q10/0635
摘要： A computer-implemented method includes receiving a new data record associated with a transaction, and generating, using an adaptive model executed by the computer, a score to represent a likelihood that the transaction is associated with fraud. The adaptive model employs feedback from one or more external data sources, the feedback containing information about one or more previous data records associated with fraud and non-fraud by at least one of the one or more external data sources. Further, the adaptive model uses the information about the one or more previous data records as input variables to update scoring parameters used to generate the score for the new data record.
摘要翻译：计算机实现的方法包括接收与事务相关联的新数据记录，以及使用由计算机执行的自适应模型生成分数以表示交易与欺诈相关联的可能性。自适应模型采用来自一个或多个外部数据源的反馈，反馈包含关于一个或多个外部数据源中的至少一个的与欺诈和非欺诈相关联的一个或多个先前数据记录的信息。此外，自适应模型使用关于一个或多个先前数据记录的信息作为输入变量来更新用于生成新数据记录的得分的评分参数。

5. 发明授权

US08645301B2 Automated entity identification for efficient profiling in an event probability prediction system 有权
标题翻译：自动实体识别用于事件概率预测系统中的高效分析
公开(公告)号：US08645301B2
公开(公告)日：2014-02-04
申请号：US13710423
申请日：2012-12-10
申请人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott M. Zoldi , Shane De Zilwa
发明人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott M. Zoldi , Shane De Zilwa
IPC分类号： G06F17/00 , G06N5/02
CPC分类号： G06N5/02 , G06N99/005 , G06Q40/00
摘要： A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.
摘要翻译：一种用于自动化实体识别的计算机实现的方法和系统，用于事件概率预测系统中的有效分析。定义属于一个或多个实体类的实体的第一子集。基于实体的第一子集中的每个实体的事务行为的一组可能结果，为实体子集中的每个实体构建至少一个历史简档。基于历史概况，选择具有与交易相关联的交易行为的实体的第二子集，所述交易行为从所述一组可能结果中预测至少一个目标结果。实体的第一个子集与第二个实体子集重新定义。

6. 发明申请

US20130103629A1 Automated Entity Identification for Efficient Profiling in an Event Probability Prediction System 有权
标题翻译：事件概率预测系统中高效分析的自动实体识别
公开(公告)号：US20130103629A1
公开(公告)日：2013-04-25
申请号：US13710423
申请日：2012-12-10
申请人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
发明人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
IPC分类号： G06N5/02
CPC分类号： G06N5/02 , G06N99/005 , G06Q40/00
摘要： A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.
摘要翻译：一种用于自动化实体识别的计算机实现的方法和系统，用于事件概率预测系统中的有效分析。定义属于一个或多个实体类的实体的第一子集。基于实体的第一子集中的每个实体的事务行为的一组可能结果，为实体子集中的每个实体构建至少一个历史简档。基于历史概况，选择具有与交易相关联的交易行为的实体的第二子集，所述交易行为从所述一组可能结果中预测至少一个目标结果。实体的第一个子集与第二个实体子集重新定义。

7. 发明申请

US20120173465A1 Automatic Variable Creation For Adaptive Analytical Models 有权
标题翻译：自适应分析模型自动变量创建
公开(公告)号：US20120173465A1
公开(公告)日：2012-07-05
申请号：US12982819
申请日：2010-12-30
申请人： Prodip Hore , Scott M. Zoldi , Larry Peranich
发明人： Prodip Hore , Scott M. Zoldi , Larry Peranich
IPC分类号： G06F15/18
CPC分类号： G06N99/005
摘要： A system and method for automated variable creation for adaptive fraud analytics are disclosed. A data structure for creation of rules is generated. The data structure represents nodes and associations between nodes from inputs for fraud/non-fraud conditions, and is generated from fraud and non-fraud data collected in an adaptive modeling process from past transactions. All unique paths between nodes of the data structure are determined to define a rule for each path. Each rule is then converted to a binary indicator variable to generate a set of binary indicator variables, and one or more complex variables is derived from the set of binary indicator variables. The one or more binary indicator variables and one or more complex variables can be provided to an adaptive scoring engine to score new transactions or to predict future behaviors.
摘要翻译：公开了一种用于自适应欺诈分析的自动变量创建的系统和方法。生成用于创建规则的数据结构。数据结构表示来自用于欺诈/非欺诈条件的输入的节点之间的节点和关联，并且是从在过去交易中的自适应建模过程中收集的欺诈和非欺诈数据产生的。确定数据结构节点之间的所有唯一路径，以定义每个路径的规则。然后将每个规则转换为二进制指示符变量以生成一组二进制指示符变量，并从一组二进制指示符变量中导出一个或多个复杂变量。可以将一个或多个二进制指示符变量和一个或多个复杂变量提供给自适应评分引擎以评估新交易或预测未来行为。

8. 发明授权

US08121962B2 Automated entity identification for efficient profiling in an event probability prediction system 有权
标题翻译：自动实体识别用于事件概率预测系统中的高效分析
公开(公告)号：US08121962B2
公开(公告)日：2012-02-21
申请号：US12110261
申请日：2008-04-25
申请人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
发明人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
IPC分类号： G06F15/18 , G06E1/00 , G06E3/00 , G06G7/00
CPC分类号： G06N5/02 , G06N99/005 , G06Q40/00
摘要： A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.
摘要翻译：一种用于自动化实体识别的计算机实现的方法和系统，用于事件概率预测系统中的有效分析。定义属于一个或多个实体类的实体的第一子集。基于实体的第一子集中的每个实体的事务行为的一组可能结果，为实体子集中的每个实体构建至少一个历史简档。基于历史简档，选择具有与交易相关联的交易行为的实体的第二子集，所述交易行为从所述一组可能结果中预测至少一个目标结果。实体的第一个子集与第二个实体子集重新定义。

9. 发明授权

US08676726B2 Automatic variable creation for adaptive analytical models 有权
标题翻译：自适应分析模型自动变量创建
公开(公告)号：US08676726B2
公开(公告)日：2014-03-18
申请号：US12982819
申请日：2010-12-30
申请人： Prodip Hore , Scott M. Zoldi , Larry Peranich
发明人： Prodip Hore , Scott M. Zoldi , Larry Peranich
IPC分类号： G06F15/18
CPC分类号： G06N99/005
摘要： A system and method for automated variable creation for adaptive fraud analytics are disclosed. A data structure for creation of rules is generated. The data structure represents nodes and associations between nodes from inputs for fraud/non-fraud conditions, and is generated from fraud and non-fraud data collected in an adaptive modeling process from past transactions. All unique paths between nodes of the data structure are determined to define a rule for each path. Each rule is then converted to a binary indicator variable to generate a set of binary indicator variables, and one or more complex variables is derived from the set of binary indicator variables. The one or more binary indicator variables and one or more complex variables can be provided to an adaptive scoring engine to score new transactions or to predict future behaviors.
摘要翻译：公开了一种用于自适应欺诈分析的自动变量创建的系统和方法。生成用于创建规则的数据结构。数据结构表示来自用于欺诈/非欺诈条件的输入的节点之间的节点和关联，并且是从在过去的交易中的自适应建模过程中收集的欺诈和非欺诈数据产生的。确定数据结构节点之间的所有唯一路径，以定义每个路径的规则。然后将每个规则转换为二进制指示符变量以生成一组二进制指示符变量，并从一组二进制指示符变量中导出一个或多个复杂变量。可以将一个或多个二进制指示符变量和一个或多个复杂变量提供给自适应评分引擎以评估新交易或预测未来行为。

10. 发明申请

US20090271343A1 Automated entity identification for efficient profiling in an event probability prediction system 有权
标题翻译：自动实体识别用于事件概率预测系统中的高效分析
公开(公告)号：US20090271343A1
公开(公告)日：2009-10-29
申请号：US12110261
申请日：2008-04-25
申请人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
发明人： Anthony Vaiciulis , Larry Peranich , Uwe Mayer , Scott Zoldi , Shane De Zilwa
IPC分类号： G06N5/00
CPC分类号： G06N5/02 , G06N99/005 , G06Q40/00
摘要： A computer-implemented method and system for automated entity identification for efficient profiling in an event probability prediction system. A first subset of entities belonging to one or more entity classes is defined. At least one historical profile is constructed for each entity in the subset of entities based on a set of possible outcomes of transaction behavior of each entity in the first subset of entities. Based on the historical profiles, a second subset of entities having transaction behavior associated with a transaction is selected, the transaction behavior being predictive of at least one targeted outcome from the set of possible outcomes. The first subset of entities is redefined with the second subset of entities.
摘要翻译：一种用于自动化实体识别的计算机实现的方法和系统，用于事件概率预测系统中的有效分析。定义属于一个或多个实体类的实体的第一子集。基于实体的第一子集中的每个实体的事务行为的一组可能结果，为实体子集中的每个实体构建至少一个历史简档。基于历史概况，选择具有与交易相关联的交易行为的实体的第二子集，所述交易行为从所述一组可能结果中预测至少一个目标结果。实体的第一个子集与第二个实体子集重新定义。

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