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公开(公告)号:US10339606B2
公开(公告)日:2019-07-02
申请号:US15258880
申请日:2016-09-07
发明人: Kamal Gupta , Vidit Jain
摘要: The systems and methods herein may include receiving a plurality of transactions for a plurality of consumers, wherein each respective transaction of the plurality of transactions is between a consumer of the plurality of consumers and a merchant of a plurality of merchants; automatically inputting the plurality of transactions into a neural network; automatically analyzing the plurality of transactions over a plurality of iterations, wherein an iteration of the plurality of iterations comprises cycling through a consumer transaction history associated with the consumer, wherein the consumer transaction history has a consumer transaction sequence associated with the consumer; and automatically updating over the plurality of iterations, a previous fraud detection variable associated with the consumer and/or the merchant to generate updated fraud detection variables, in response to the analyzing the plurality of transactions.
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公开(公告)号:US11900401B2
公开(公告)日:2024-02-13
申请号:US18314668
申请日:2023-05-09
发明人: Lee Chau , Tirthankar Choudhuri , Ajay Choudhary , Vikas Grover , Mohd Arshad Naeem , Subhajit Sanyal , Dawn Thomas , Amit Jagdish Agarwal , Pranav Mehta , Kamal Gupta , Subhra Purkayastha , Prakruthi Prabhakar
IPC分类号: G06Q30/00 , G06Q30/0204 , G06Q30/0251 , G06Q30/0601
CPC分类号: G06Q30/0204 , G06Q30/0254 , G06Q30/0631
摘要: The present disclosure presents systems and related methods for creating real-time predictions. One such method comprises receiving, by a computing device, a first set of data and a second set of data, wherein the first set of data comprises a plurality of items available from a first source for a first set of users and the second set of data comprises transaction purchase data for a second set of users that have reward accounts, utilizing a predictive data model that determines a propensity score for a user from only behavior data that is not attributed to the user; receiving a third set of data from a third source comprising social media channel data for a third set of users; and updating the predictive data model to determine the propensity score for the user based at least in part on the third set of data.
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公开(公告)号:US11710140B1
公开(公告)日:2023-07-25
申请号:US16748451
申请日:2020-01-21
发明人: Lee Chau , Tirthankar Choudhuri , Ajay Choudhary , Vikas Grover , Mohd Arshad Naeem , Subhajit Sanyal , Dawn Thomas , Amit Jagdish Agarwal , Pranav Mehta , Kamal Gupta , Subhra Purkayastha , Prakruthi Prabhakar
IPC分类号: G06Q30/00 , G06Q30/0204 , G06Q30/0251 , G06Q30/0601
CPC分类号: G06Q30/0204 , G06Q30/0254 , G06Q30/0631
摘要: The systems, methods and computer program products (collectively “system”) described herein relate to customized real time data delivery. The system may be configured to receive, by a performance marketing cluster, first data from a first data source. The system may also receive, by the performance marketing cluster, second data from a second data source. The system may determine, by the marketing cluster, an analysis scheme for the first data and the second data based on the first data source. The system may also determine, by the marketing cluster, at least one of a propensity to act or a recommendation selected from a predefined number of available options for a population based on the analysis scheme and the first data source.
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公开(公告)号:US10956987B2
公开(公告)日:2021-03-23
申请号:US16426826
申请日:2019-05-30
发明人: Kamal Gupta , Vidit Jain
摘要: The systems and methods herein may include receiving a plurality of transactions for a plurality of consumers, wherein each respective transaction of the plurality of transactions is between a consumer of the plurality of consumers and a merchant of a plurality of merchants; automatically inputting the plurality of transactions into a neural network; automatically analyzing the plurality of transactions over a plurality of iterations, wherein an iteration of the plurality of iterations comprises cycling through a consumer transaction history associated with the consumer, wherein the consumer transaction history has a consumer transaction sequence associated with the consumer; and automatically updating over the plurality of iterations, a previous fraud detection variable associated with the consumer and/or the merchant to generate updated fraud detection variables, in response to the analyzing the plurality of transactions.
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公开(公告)号:US20190279309A1
公开(公告)日:2019-09-12
申请号:US16426826
申请日:2019-05-30
发明人: Kamal Gupta , Vidit Jain
摘要: The systems and methods herein may include receiving a plurality of transactions for a plurality of consumers, wherein each respective transaction of the plurality of transactions is between a consumer of the plurality of consumers and a merchant of a plurality of merchants; automatically inputting the plurality of transactions into a neural network; automatically analyzing the plurality of transactions over a plurality of iterations, wherein an iteration of the plurality of iterations comprises cycling through a consumer transaction history associated with the consumer, wherein the consumer transaction history has a consumer transaction sequence associated with the consumer; and automatically updating over the plurality of iterations, a previous fraud detection variable associated with the consumer and/or the merchant to generate updated fraud detection variables, in response to the analyzing the plurality of transactions.
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公开(公告)号:US20230306452A1
公开(公告)日:2023-09-28
申请号:US18314668
申请日:2023-05-09
发明人: Lee Chau , Tirthankar Choudhuri , Ajay Choudhary , Vikas Grover , Mohd Arshad Naeem , Subhajit Sanyal , Dawn Thomas , Amit Jagdish Agarwal , Pranav Mehta , Kamal Gupta , Subhra Purkayastha , Prakruthi Prabhakar
IPC分类号: G06Q30/0204 , G06Q30/0251 , G06Q30/0601
CPC分类号: G06Q30/0204 , G06Q30/0254 , G06Q30/0631
摘要: The present disclosure presents systems and related methods for creating real-time predictions. One such method comprises receiving, by a computing device, a first set of data and a second set of data, wherein the first set of data comprises a plurality of items available from a first source for a first set of users and the second set of data comprises transaction purchase data for a second set of users that have reward accounts, utilizing a predictive data model that determines a propensity score for a user from only behavior data that is not attributed to the user; receiving a third set of data from a third source comprising social media channel data for a third set of users; and updating the predictive data model to determine the propensity score for the user based at least in part on the third set of data.
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公开(公告)号:US20180068395A1
公开(公告)日:2018-03-08
申请号:US15258880
申请日:2016-09-07
发明人: Kamal Gupta , Vidit Jain
摘要: The systems and methods herein may include receiving a plurality of transactions for a plurality of consumers, wherein each respective transaction of the plurality of transactions is between a consumer of the plurality of consumers and a merchant of a plurality of merchants; automatically inputting the plurality of transactions into a neural network; automatically analyzing the plurality of transactions over a plurality of iterations, wherein an iteration of the plurality of iterations comprises cycling through a consumer transaction history associated with the consumer, wherein the consumer transaction history has a consumer transaction sequence associated with the consumer; and automatically updating over the plurality of iterations, a previous fraud detection variable associated with the consumer and/or the merchant to generate updated fraud detection variables, in response to the analyzing the plurality of transactions.
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公开(公告)号:US20170046727A1
公开(公告)日:2017-02-16
申请号:US14961614
申请日:2015-12-07
发明人: Lee Chau , Tirthankar Choudhuri , Ajay Choudhary , Vikas Grover , Mohd Arshad Naeem , Subhajit Sanyal , Dawn Thomas , Amit Jagdish Agarwal , Pranav Mehta , Kamal Gupta , Subhra Purkayastha , Prakruthi Prabhakar
CPC分类号: G06Q30/0204 , G06Q30/0254 , G06Q30/0631
摘要: The systems, methods and computer program products (collectively “system”) described herein relate to customized real time data delivery. The system may be configured to receive, by a performance marketing cluster, first data from a first data source. The system may also receive, by the performance marketing cluster, second data from a second data source. The system may determine, by the marketing cluster, an analysis scheme for the first data and the second data based on the first data source. The system may also determine, by the marketing cluster, at least one of a propensity to act or a recommendation selected from a predefined number of available options for a population based on the analysis scheme and the first data source.
摘要翻译: 这里描述的系统,方法和计算机程序产品(统称为“系统”)涉及定制的实时数据传送。 该系统可以被配置为通过性能营销集群从第一数据源接收第一数据。 该系统还可以由性能营销集群从第二数据源接收第二数据。 该系统可以由营销群集基于第一数据源确定第一数据和第二数据的分析方案。 该系统还可以通过营销集群,基于分析方案和第一数据源,确定从群体的预定数量的可用选项中选择的行动倾向或推荐中的至少一个。
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