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公开(公告)号：US08768743B2
公开(公告)日：2014-07-01
申请号：US11625247
申请日：2007-01-19
申请人： Shailesh Kumar , Stuart Crawford , Sergei Tolmanov , Megan Thorsen , Helen Geraldine E Rosario , Ashutosh Joshi , Victor Miagkikh , Colin Little
发明人： Shailesh Kumar , Stuart Crawford , Sergei Tolmanov , Megan Thorsen , Helen Geraldine E Rosario , Ashutosh Joshi , Victor Miagkikh , Colin Little
IPC分类号： G06F17/30
CPC分类号： G06Q30/02 , G06Q30/0601 , G06Q30/0603
摘要： A product space browser (PSB), which comprises a graphical user interface (GUI) that facilitates insight discovery through exploration and analysis of product space graphs generated by applying a product affinity engine to retailer's transaction data in a market basket context, is disclosed.
摘要翻译： 公开了一种产品空间浏览器（PSB），其包括图形用户界面（GUI），其通过对通过在市场篮子上下文中对零售商的交易数据应用产品亲和度引擎而产生的产品空间图的探索和分析来促进洞察发现。
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公开(公告)号：US08255423B2
公开(公告)日：2012-08-28
申请号：US12430818
申请日：2009-04-27
申请人： Christopher Allan Ralph , Michael S. Sossi , Stefan Kuzminski , Helen Geraldine E. Rosario , Yaxin Liu
发明人： Christopher Allan Ralph , Michael S. Sossi , Stefan Kuzminski , Helen Geraldine E. Rosario , Yaxin Liu
IPC分类号： G06F7/00
CPC分类号： G06Q10/10
摘要： A system and method for building segmented scorecards for a population is presented. A model of the population is built using a model builder computer, and one or more variables used by the model builder to build the model is stored in a repository. A scorecard is generated for each segment of the population based on the model and using an adaptive random tree computer program. Next, the scorecard for each segment is enhanced using a integer non-linear programming computer program to determine optimal score weights associated with the variables used by the model builder to build the model, and to generate an enhanced segmented scorecard for the population.
摘要翻译： 提出了一种为人口建立分段记分卡的系统和方法。 使用模型构建器计算机构建人口模型，模型构建器用于构建模型的一个或多个变量存储在存储库中。 基于模型并使用自适应随机树计算机程序为每个群体生成记分卡。 接下来，使用整数非线性规划计算机程序来增强每个段的记分卡，以确定与由模型构建器构建模型所使用的变量相关联的最佳分数权重，并为群体生成增强的分段记分卡。
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公开(公告)号：US20100049538A1
公开(公告)日：2010-02-25
申请号：US12197134
申请日：2008-08-22
IPC分类号： G06Q99/00
CPC分类号： G06Q30/0201 , G06Q30/02 , G06Q30/0241 , G06Q30/0244
摘要： A method for selecting a next action includes reading transaction data, determining insights and relationships between a first entity and a second entity from the collected transaction data. Once these relationships and insights have been determined, the possibility of a future event occurring in one of a number of selected time periods can be determined using a predictive time-to-event component. A system for selecting a next action includes a memory for storing transaction data, an insight/relationship determination module, and a predictive time-to-event module. The memory, the insight/relationship determination module and the predictive time-to-event module carry out the above method. A programmable media having an instruction set can also cause a machine to carry out the above method.
摘要翻译： 用于选择下一个动作的方法包括从所收集的交易数据读取交易数据，确定第一实体和第二实体之间的见解和关系。 一旦确定了这些关系和见解，可以使用预测时间到事件组件来确定在多个选定时间段之一中发生的未来事件的可能性。 用于选择下一个动作的系统包括用于存储交易数据的存储器，洞察/关系确定模块和预测时间到事件模块。 存储器，洞察/关系确定模块和预测时间到事件模块执行上述方法。 具有指令集的可编程媒体也可使机器执行上述方法。
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公开(公告)号：US20080177681A1
公开(公告)日：2008-07-24
申请号：US11877626
申请日：2007-10-23
IPC分类号： G06N3/12
CPC分类号： G06N3/126
摘要： Data spiders, provide an automated system that can take a file or file store of historic transaction data and create the best set of variables from that data, where “best” means highly predictive. Genetic algorithms are used to parameterized transactions to form groups, which are subjected naïve Bayes score ranking. Variable groups are generated and ranked accord to the score. Data spiders span the full information available, are uncorrelated with previous methods, and are easily interpretable.
摘要翻译： 数据蜘蛛提供了一个自动化系统，可以获取历史交易数据的文件或文件存储，并从该数据中创建最佳的变量集，其中“最佳”意味着高度预测。 遗传算法用于参数化交易以形成组，其受到朴素的贝叶斯评分排名。 生成变量组并按照得分排序。 数据蜘蛛涵盖了可用的全部信息，与以前的方法不相关，并且易于解释。
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公开(公告)号：US20100287167A1
公开(公告)日：2010-11-11
申请号：US12430818
申请日：2009-04-27
申请人： Christopher Allan Ralph , Michael S. Sossi , Stefan Kuzminski , Helen Geraldine E. Rosario , Yaxin Liu
发明人： Christopher Allan Ralph , Michael S. Sossi , Stefan Kuzminski , Helen Geraldine E. Rosario , Yaxin Liu
IPC分类号： G06F17/30
CPC分类号： G06Q10/10
摘要： A system and method for building segmented scorecards for a population is presented. A model of the population is built using a model builder computer, and one or more variables used by the model builder to build the model is stored in a repository. A scorecard is generated for each segment of the population based on the model and using an adaptive random tree computer program. Next, the scorecard for each segment is enhanced using a integer non-linear programming computer program to determine optimal score weights associated with the variables used by the model builder to build the model, and to generate an enhanced segmented scorecard for the population.
摘要翻译： 提出了一种为人口建立分段记分卡的系统和方法。 使用模型构建器计算机构建人口模型，模型构建器用于构建模型的一个或多个变量存储在存储库中。 基于模型并使用自适应随机树计算机程序为每个群体生成记分卡。 接下来，使用整数非线性规划计算机程序来增强每个段的记分卡，以确定与由模型构建器构建模型所使用的变量相关联的最佳分数权重，并为群体生成增强的分段记分卡。
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公开(公告)号：US20070282699A1
公开(公告)日：2007-12-06
申请号：US11551683
申请日：2006-10-20
申请人： Shailesh Kumar , Megan Thorsen , Ashutosh Joshi , Sergei Tolmanov , Helen Geraldine E. Rosario , Colin E. Little
发明人： Shailesh Kumar , Megan Thorsen , Ashutosh Joshi , Sergei Tolmanov , Helen Geraldine E. Rosario , Colin E. Little
IPC分类号： G06Q30/00
CPC分类号： G06Q30/02 , G06Q30/0601 , G06Q30/0625 , G06Q30/0633 , G06Q30/0641 , G06Q30/0643 , G06Q40/04
摘要： The invention provides a purchase sequence browser (PuSB), i.e. a graphical user interface (GUI) that facilitates insight discovery and exploration of product affinities across time, generated by a purchase sequence analysis of a retailer's transaction data. A purchase sequence browser allows the user to browse the most significant product phrases discovered by an exhaustive search of the product affinities across time; explore the retail grammar to create both forward and backward phrase trees or alternate purchase paths starting from, or ending in, a product; generate consistent purchase sequences given some constraints on the products and their order; and profile the value of a product across time with regard to other products fixed in time.
摘要翻译： 本发明提供了购买序列浏览器（PuSB），即图形用户界面（GUI），其通过零售商的交易数据的购买序列分析产生的促进对时间的产品亲和力的洞察发现和探索。 购买序列浏览器允许用户浏览通过对产品亲和力的详尽搜索发现的最重要的产品短语; 探索零售语法，从产品开始或结束时创建向前和向后的短语树或替代购买路径; 产生一致的采购顺序，给产品及其顺序带来一些限制; 并对与其他产品及时相关的产品的价值进行分析。
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公开(公告)号：US07962368B2
公开(公告)日：2011-06-14
申请号：US11551683
申请日：2006-10-20
申请人： Shailesh Kumar , Megan Thorsen , Ashutosh Joshi , Sergei Tolmanov , Helen Geraldine E Rosario , Colin E Little
发明人： Shailesh Kumar , Megan Thorsen , Ashutosh Joshi , Sergei Tolmanov , Helen Geraldine E Rosario , Colin E Little
IPC分类号： G06Q30/00
CPC分类号： G06Q30/02 , G06Q30/0601 , G06Q30/0625 , G06Q30/0633 , G06Q30/0641 , G06Q30/0643 , G06Q40/04
摘要： The invention provides a purchase sequence browser (PuSB), i.e. a graphical user interface (GUI) that facilitates insight discovery and exploration of product affinities across time, generated by a purchase sequence analysis of a retailer's transaction data. A purchase sequence browser allows the user to browse the most significant product phrases discovered by an exhaustive search of the product affinities across time; explore the retail grammar to create both forward and backward phrase trees or alternate purchase paths starting from, or ending in, a product; generate consistent purchase sequences given some constraints on the products and their order; and profile the value of a product across time with regard to other products fixed in time.
摘要翻译： 本发明提供了购买序列浏览器（PuSB），即图形用户界面（GUI），其通过零售商的交易数据的购买序列分析产生的促进对时间的产品亲和力的洞察发现和探索。 购买序列浏览器允许用户浏览通过对产品亲和力的详尽搜索发现的最重要的产品短语; 探索零售语法，从产品开始或结束时创建向前和向后的短语树或替代购买路径; 产生一致的采购顺序，给产品及其顺序带来一些限制; 并对与其他产品及时相关的产品的价值进行分析。
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公开(公告)号：US07895139B2
公开(公告)日：2011-02-22
申请号：US11877626
申请日：2007-10-23
申请人： Gary J. Sullivan , Helen Geraldine E. Rosario , Michael S. Sossi , Christopher Ralph , John Duchnowski
发明人： Gary J. Sullivan , Helen Geraldine E. Rosario , Michael S. Sossi , Christopher Ralph , John Duchnowski
IPC分类号： G06N5/00
CPC分类号： G06N3/126
摘要： Data spiders, provide an automated system that can take a file or file store of historic transaction data and create the best set of variables from that data, where “best” means highly predictive. Genetic algorithms are used to parameterized transactions to form groups, which are subjected naïve Bayes score ranking. Variable groups are generated and ranked accord to the score. Data spiders span the full information available, are uncorrelated with previous methods, and are easily interpretable.
摘要翻译： 数据蜘蛛提供了一个自动化系统，可以获取历史交易数据的文件或文件存储，并从该数据中创建最佳的变量集，其中“最佳”意味着高度预测。 遗传算法用于参数化交易以形成组，其受到朴素的贝叶斯评分排名。 生成变量组并按照得分排序。 数据蜘蛛涵盖了可用的全部信息，与以前的方法不相关，并且易于解释。
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