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公开(公告)号：US20150066566A1
公开(公告)日：2015-03-05
申请号：US14015592
申请日：2013-08-30
IPC分类号： G06Q10/06
CPC分类号： G06Q10/06315
摘要： A method for balancing supply and demand for a product using demand-shaping action includes identifying an imbalance between supply and demand for a given product. A customer choice model is generated based on collected historical sales data pertaining to the given product and at least one product similar to the given product. The customer choice model is configured to estimate, for a given customer or group of customers, a likelihood of effecting a substitution between each product pair of the given product and the at least one product similar to the given product, for each of one or more available demand shaping actions. One or more of the available demand shaping actions are automatically selected to minimize an estimate of revenue shortfall or inventory holding costs resulting from the identified imbalance between supply and demand.
摘要翻译： 使用需求整形作用来平衡产品供需的方法包括识别给定产品的供应和需求之间的不平衡。 基于收集的与给定产品有关的历史销售数据和至少一种类似于给定产品的产品生成客户选择模型。 客户选择模型被配置为针对给定的客户或一组客户估计在给定产品的每个产品对与类似于给定产品的至少一个产品之间进行替换的可能性，对于一个或多个 可用需求整形动作。 自动选择一个或多个可用的需求整形操作，以最大限度地减少由于供应和需求之间的不均衡导致的收入不足或库存持有成本的估计。
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公开(公告)号：US11151604B2
公开(公告)日：2021-10-19
申请号：US15179271
申请日：2016-06-10
IPC分类号： G06Q30/02
摘要： Systems, methods, and computer-readable media for controlling the timing of customer interactions (e.g., targeted product or service offerings to customers) in order to determine optimally efficient usage of a seller's available inventory are disclosed. A customer selection problem (CSP) may be formulated and solved to implement a customer selection policy for controlling the timing with which customers from a customer pool will be targeted with offerings. The customer selection policy may include dynamic optimization to account for intertemporal effects of customer decisions.
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公开(公告)号：US20170116531A1
公开(公告)日：2017-04-27
申请号：US14924014
申请日：2015-10-27
发明人： Chitra Dorai , Roger D. Lederman , Ying Li
CPC分类号： G06N20/00 , G06Q40/025
摘要： A method, system and computer program product for detecting an emerging life event and identifying an action plan to remediate affects of the life event are disclosed. In an embodiment, the method comprises specifying a group of emerging life events, and a group of behavior features that map to the emerging life events; receiving behavioral data identifying behavior of a person; and analyzing the behavioral data to determine if any of the specified behavior features are identified in the behavioral data. When one or more of the behavior feature are identified in the behavioral data as behavior features of the person, the identified behavior features are mapped to one or more of the specified emerging life events; and the mapped emerging life events is used to determine an action plan to remediate affects of that life event.
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4.发明授权公开(公告)号：US11176492B2
公开(公告)日：2021-11-16
申请号：US16352958
申请日：2019-03-14
发明人： Pawan R. Chowdhary , Markus R. Ettl , Roger D. Lederman , Tim Nonner , Ulrich B. Schimpel , Zhengliang Xue , Hongxia Yang
摘要： A machine learning algorithm is trained to learn to cluster a plurality of original-destination routes in a network for transporting cargo into a plurality of clusters based on similarities of the original-destination routes, and to learn to cluster the plurality of clusters into a plurality of subgroups based on customer behavior. Influencing criteria associated with each of the subgroups may be determined and based on the influencing criteria, a price elasticity curve for each of the subgroups may be generated. Based on the price elasticity curve and current network traffic, cargo transportation price associated with each of the subgroups may be determined.
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5.发明申请公开(公告)号：US20180121829A1
公开(公告)日：2018-05-03
申请号：US15340548
申请日：2016-11-01
发明人： Pawan R. Chowdhary , Markus R. Ettl , Roger D. Lederman , Tim Nonner , Ulrich B. Schimpel , Zhengliang Xue , Hongxia Yang
IPC分类号： G06N99/00
摘要： A machine learning algorithm is trained to learn to cluster a plurality of original-destination routes in a network for transporting cargo into a plurality of clusters based on similarities of the original-destination routes, and to learn to cluster the plurality of clusters into a plurality of subgroups based on customer behavior. Influencing criteria associated with each of the subgroups may be determined and based on the influencing criteria, a price elasticity curve for each of the subgroups may be generated. Based on the price elasticity curve and current network traffic, cargo transportation price associated with each of the subgroups may be determined.
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公开(公告)号：US10572890B2
公开(公告)日：2020-02-25
申请号：US14814027
申请日：2015-07-30
摘要： System, method and computer program product for effective supply-side planning of inventories during product transitions. The system for a supply-side entity that generates recommendations that include personalized shaping actions to control each customer's rate of adoption of a new product to replace an older legacy product during a transition period, and optimize overall use of available supply. The method optimizes personalized shaping actions so that a customer is transitioned at a speed that suits their personal profile as well as the seller's production/inventory constraints for each product. Shaping actions are determined based on the trajectory of each product's lifecycle. Further, customer-level adoption patterns for transitioning products are predicted from past behavior.
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7.发明申请公开(公告)号：US20190213500A1
公开(公告)日：2019-07-11
申请号：US16352958
申请日：2019-03-14
发明人： Pawan R. Chowdhary , Markus R. Ettl , Roger D. Lederman , Tim Nonner , Ulrich B. Schimpel , Zhengliang Xue , Hongxia Yang
摘要： A machine learning algorithm is trained to learn to cluster a plurality of original-destination routes in a network for transporting cargo into a plurality of clusters based on similarities of the original-destination routes, and to learn to cluster the plurality of clusters into a plurality of subgroups based on customer behavior. Influencing criteria associated with each of the subgroups may be determined and based on the influencing criteria, a price elasticity curve for each of the subgroups may be generated. Based on the price elasticity curve and current network traffic, cargo transportation price associated with each of the subgroups may be determined.
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公开(公告)号：US20180082253A1
公开(公告)日：2018-03-22
申请号：US15270364
申请日：2016-09-20
CPC分类号： G06Q10/08345 , G06Q10/1095
摘要： System and method that improves cargo logistics may be presented. For instance, shipping capacity in cargo logistics may be best utilized based on providing pricing and scheduling solutions that are jointly optimized and prices differentiated based on flexibility of service request. Scheduled service and pricing may be transmitted as a signal to control execution of the cargo logistics.
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公开(公告)号：US20170358001A1
公开(公告)日：2017-12-14
申请号：US15179271
申请日：2016-06-10
发明人： Adam Elmachtoub , Roger D. Lederman
IPC分类号： G06Q30/02
CPC分类号： G06Q30/0247 , G06Q30/0264
摘要： Systems, methods, and computer-readable media for controlling the timing of customer interactions (e.g., targeted product or service offerings to customers) in order to determine optimally efficient usage of a seller's available inventory are disclosed. A customer selection problem (CSP) may be formulated and solved to implement a customer selection policy for controlling the timing with which customers from a customer pool will be targeted with offerings. The customer selection policy may include dynamic optimization to account for intertemporal effects of customer decisions.
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公开(公告)号：US10692039B2
公开(公告)日：2020-06-23
申请号：US15270364
申请日：2016-09-20
摘要： System and method that improves cargo logistics may be presented. For instance, shipping capacity in cargo logistics may be best utilized based on providing pricing and scheduling solutions that are jointly optimized and prices differentiated based on flexibility of service request. Scheduled service and pricing may be transmitted as a signal to control execution of the cargo logistics.
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