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1. 发明授权

US10055776B2 Decision making criteria-driven recommendations 有权
公开(公告)号：US10055776B2
公开(公告)日：2018-08-21
申请号：US13959049
申请日：2013-08-05
申请人： Philippe Nemery , Wen-Syan Li
发明人： Philippe Nemery , Wen-Syan Li
IPC分类号： G06Q30/00 , G06Q30/06
CPC分类号： G06Q30/0631 , G06Q30/0601 , G06Q30/0623 , G06Q30/0629 , G06Q30/0641
摘要： The embodiments provide a system for decision-making criteria-based recommendations. The system may include a decision engine configured to receive a request for recommendations for an option problem associated with a product or service category, and determine options among a plurality of options for the product or service category based on preference information. The preference information may include activated decision-making criteria and corresponding weight values. The corresponding weight values may represent a relative importance of each activated decision-making criterion. The decision engine may be configured to determine options among the plurality of options including calculating scores for the plurality of options based on, in part, the activated decision-making criteria and the corresponding weight values and selecting the options among the plurality of options based on the calculated scores. The decision engine may be configured to provide a display of the determined options as the recommendations for the product or service category.

2. 发明申请

US20160055494A1 BOOKING BASED DEMAND FORECAST 审中-公开
标题翻译：基于预期的需求预测
公开(公告)号：US20160055494A1
公开(公告)日：2016-02-25
申请号：US14463199
申请日：2014-08-19
申请人： Boyi Ni , Ruijiang Li , Wenyu Dong , Xingtian Shi , Philippe Nemery , Terry Wang , Irene Chen , Mark Finch , Harald Hengelbrock
发明人： Boyi Ni , Ruijiang Li , Wenyu Dong , Xingtian Shi , Philippe Nemery , Terry Wang , Irene Chen , Mark Finch , Harald Hengelbrock
IPC分类号： G06Q30/02 , G06Q10/02
CPC分类号： G06Q30/0202 , G06Q10/02
摘要： A computer-implemented method for a booking based demand forecast problem includes converting time series data into a multivariate time series, training a multivariate time series model using the converted multivariate time series, forecasting results using the multivariate time series model and aggregating the results.
摘要翻译：用于基于预约的需求预测问题的计算机实现方法包括将时间序列数据转换为多变量时间序列，使用转换的多变量时间序列训练多变量时间序列模型，使用多变量时间序列模型预测结果并聚合结果。

3. 发明申请

US20140379520A1 DECISION MAKING CRITERIA-DRIVEN RECOMMENDATIONS 审中-公开
标题翻译：决定制定标准驱动的建议
公开(公告)号：US20140379520A1
公开(公告)日：2014-12-25
申请号：US13959049
申请日：2013-08-05
申请人： Philippe Nemery , Wen-Syan Li
发明人： Philippe Nemery , Wen-Syan Li
IPC分类号： G06Q30/06
CPC分类号： G06Q30/0631 , G06Q30/0601 , G06Q30/0623 , G06Q30/0629 , G06Q30/0641
摘要： The embodiments provide a system for decision-making criteria-based recommendations. The system may include a decision engine configured to receive a request for recommendations for an option problem associated with a product or service category, and determine options among a plurality of options for the product or service category based on preference information. The preference information may include activated decision-making criteria and corresponding weight values. The corresponding weight values may represent a relative importance of each activated decision-making criterion. The decision engine may be configured to determine options among the plurality of options including calculating scores for the plurality of options based on, in part, the activated decision-making criteria and the corresponding weight values and selecting the options among the plurality of options based on the calculated scores. The decision engine may be configured to provide a display of the determined options as the recommendations for the product or service category.
摘要翻译：这些实施例提供了一种用于基于决策的基于标准的建议的系统。系统可以包括被配置为接收关于与产品或服务类别相关联的选项问题的建议的请求的决策引擎，并且基于偏好信息来确定产品或服务类别的多个选项之间的选项。偏好信息可以包括激活的决策标准和对应的权重值。相应的权重值可以表示每个激活的决策标准的相对重要性。决策引擎可以被配置为确定多个选项中的选项，包括基于部分地基于激活的决策标准和相应的权重值来计算多个选项的分数，并且基于多个选项中的选项，基于计算得分。决策引擎可以被配置为提供所确定的选项的显示作为产品或服务类别的建议。

4. 发明申请

US20160125501A1 PREFERENCE-ELICITATION FRAMEWORK FOR REAL-TIME PERSONALIZED RECOMMENDATION 审中-公开
标题翻译：用于实时个性化推荐的优先选择框架
公开(公告)号：US20160125501A1
公开(公告)日：2016-05-05
申请号：US14532677
申请日：2014-11-04
申请人： Philippe NEMERY , Boyi NI , Wen-Syan LI
发明人： Philippe NEMERY , Boyi NI , Wen-Syan LI
IPC分类号： G06Q30/06 , G06N99/00 , G06N7/00 , G06F17/30 , G06N5/04
CPC分类号： G06Q30/0631 , G06F16/24578 , G06N5/003 , G06N7/005 , G06N20/00
摘要： A system includes an option selection engine selects an initial subset of pre-selected products from multiple products for display to a user, where the products include multiple filtering options and multiple selection criteria. An elicitation engine prompts the user to provide input including input for the filtering options and input for the selection criteria and receives the filtering options input and the selection criteria input. A ranking and scoring engine receives the filtering options input and the selection criteria input and selects one method of multiple methods to calculate a score for the products and to rank the products using the score based on the filtering options input and the selection criteria input from the user. An option selection engine selects an updated subset of products from the plurality of products for display to the user based on the rank of the of the products using the score.
摘要翻译：系统包括选项选择引擎从多个产品中选择预选产品的初始子集以供显示给用户，其中产品包括多个过滤选项和多个选择标准。引导引擎提示用户提供输入，包括过滤选项的输入和选择标准的输入，并接收过滤选项输入和选择标准输入。排名和评分引擎接收过滤选项输入和选择标准输入，并选择多种方法的一种方法来计算产品的分数，并使用基于过滤选项输入的评分和从用户。选择选择引擎基于使用分数的产品的等级从多个产品中选择更新的产品子集以供显示给用户。

5. 发明申请

US20160055438A1 SYSTEM AND METHOD FOR EMPTY CONTAINER REPOSITION RESISTANT TO DISRUPTIONS 审中-公开
标题翻译：容量大的系统和方法可以抵抗破坏
公开(公告)号：US20160055438A1
公开(公告)日：2016-02-25
申请号：US14463202
申请日：2014-08-19
申请人： Yuanyuan CEN , Honggang WANG , Philippe Nemery , Yingbin ZHENG , Yan TAN
发明人： Yuanyuan CEN , Honggang WANG , Philippe Nemery , Yingbin ZHENG , Yan TAN
IPC分类号： G06Q10/06
CPC分类号： G06Q10/06315
摘要： A system for empty container repositioning includes a scenario module, a forecast engine, a network builder module and a multi-commodity flow solver. The scenario module is configured to define a plurality of scenarios related to a safe stock level of empty containers at each of multiple locations having one or more transport vessels. The forecast engine is configured to forecast values for each of the defined scenarios, where the forecasted values include a safe stock level of empty containers for each location. The network builder module is configured to use the forecasted values to build a multi-commodity flow network. The multi-commodity flow solver is configured to determine a number of empty containers to load on and load off of the transport vessels at each of the locations.
摘要翻译：用于空容器重新定位的系统包括场景模块，预测引擎，网络构建器模块和多商品流解决器。情景模块被配置为在具有一个或多个运输船只的多个位置的每个位置处定义与空容器的安全库存水平相关的多个场景。预测引擎配置为预测每个定义方案的值，其中预测值包括每个位置的空容器的安全库存水平。网络构建器模块被配置为使用预测值来构建多商品流网络。多商品流量求解器被配置为确定在每个位置处加载和卸载运输船的空容器的数量。

6. 发明申请

US20160048803A1 AUTOMATON-BASED FRAMEWORK FOR ASSET NETWORK ROUTING 审中-公开
标题翻译：基于AUTOMATON的资产网络路由框架
公开(公告)号：US20160048803A1
公开(公告)日：2016-02-18
申请号：US14459262
申请日：2014-08-13
申请人： Yuanyuan CEN , Yingbin ZHENG , Yan TAN , Honggang WANG , Philippe NEMERY , Xingtian SHI , Irene CHEN , Terry WANG , Mark Finch
发明人： Yuanyuan CEN , Yingbin ZHENG , Yan TAN , Honggang WANG , Philippe NEMERY , Xingtian SHI , Irene CHEN , Terry WANG , Mark Finch
IPC分类号： G06Q10/08
CPC分类号： G06Q10/08355 , G06Q10/08 , G06Q10/083
摘要： A rule handler may receive a first routing rule and a second routing rule, each routing rule characterizing at least one potential physical transportation route. A rule converter may convert the first routing rule and the second routing rule into a first finite automaton (FA) and a second finite automaton, respectively, and may combine the first finite automaton and the second finite automaton into a finite automaton network graph. A graph comparator may then compare the finite automaton network graph to existing physical transportation routes, and a route selector may select, based on the comparing, at least one feasible physical transportation route from the existing physical transportation routes, the at least one feasible physical transportation route being an instance of the at least one potential physical transportation route.
摘要翻译：规则处理程序可以接收第一路由规则和第二路由规则，每个路由规则表征至少一个潜在的物理传输路由。规则转换器可以将第一路由规则和第二路由规则分别转换成第一有限自动机（FA）和第二有限自动机，并且可以将第一有限自动机和第二有限自动机组合成有限自动机网络图。图形比较器然后可以将有限自动机网络图与现有物理运输路线进行比较，并且路线选择器可以基于比较，从现有物理运输路线中选择至少一条可行的物理运输路线，所述至少一条可行的物理运输路线是至少一个潜在的物理运输路线的实例。

7. 发明申请

US20160042444A1 TRANSPORT EQUIPMENT LOGISTICS 审中-公开
标题翻译：运输设备物流
公开(公告)号：US20160042444A1
公开(公告)日：2016-02-11
申请号：US14456421
申请日：2014-08-11
申请人： Harald HENGELBROCK , Mark FINCH , Irene CHEN , Xingtian SHI , Philippe NEMERY , Terry WANG
发明人： Harald HENGELBROCK , Mark FINCH , Irene CHEN , Xingtian SHI , Philippe NEMERY , Terry WANG
IPC分类号： G06Q30/06 , G06Q30/04
CPC分类号： G06Q30/0645 , G06Q30/04 , G06Q30/0635
摘要： A computer-implemented method includes receiving, at a rental company, a customer's order to hire a transport equipment unit of a first type beginning on a start date. The rental company has an inventory of transport equipment units for hire and a network of diverse storage sites. The computer-implemented method further includes locating one or more transport equipment units of the first type in the rental company's inventory of transport equipment available for hire by the start date, computing the rental company's costs associated with picking up each of the located transport equipment units of the first type for delivery to the customer, and selecting, based on consideration of the rental company's picking up costs, one of the located transport equipment units for delivery to customer.
摘要翻译：计算机实现的方法包括在租赁公司接收客户的订单以从开始日期开始雇用第一类型的运输设备单元。租赁公司有一个出租运输设备单位的库存和一个多样化的仓库网络。计算机实现的方法还包括将第一类型的一个或多个运输设备单元定位在租赁公司可用于在开始日期出租的运输设备的库存中，计算租赁公司与拾取每个定位的运输设备单元相关的成本的第一种类型，用于交付给客户，并且基于考虑到租赁公司的起运成本，选择一个位于运输设备单元以交付给客户。

8. 发明申请

US20150120731A1 PREFERENCE BASED CLUSTERING 审中-公开
标题翻译：基于偏好的聚类
公开(公告)号：US20150120731A1
公开(公告)日：2015-04-30
申请号：US14072794
申请日：2013-11-06
申请人： PHILIPPE NEMERY , Mengjiao Wang
发明人： PHILIPPE NEMERY , Mengjiao Wang
IPC分类号： G06F17/30
CPC分类号： G06F16/285
摘要： To cluster objects associated with a dataset, a selection of criteria is received. For the received criteria, preference information is received to perform a preference-based clustering of the objects. Based on the preference information, a uni-criterion preference degree corresponding to each of the selected criterion is computed. The uni-criterion preference degrees of all the selected criteria are aggregated to compute a universal preference degree. Based on a preference-type and the computed preference degree, a relationship matrix is generated. The matrix representing similarity measure between the objects is generated. The objects are clustered according to the relationship matrix. A visualization of the clustered objects is rendered on an associated user interface.
摘要翻译：要集群与数据集关联的对象，接收到选择的条件。对于接收到的标准，接收到偏好信息以执行对象的基于偏好的聚类。基于偏好信息，计算与所选择的标准中的每一个对应的单一标准偏好度。所有所选标准的单一标准偏好度被聚合以计算通用偏好度。基于偏好类型和计算的偏好度，生成关系矩阵。生成表示对象之间的相似性度量的矩阵。对象根据关系矩阵进行聚类。聚集对象的可视化在相关联的用户界面上呈现。

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