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公开(公告)号：US10579423B2
公开(公告)日：2020-03-03
申请号：US15943206
申请日：2018-04-02
发明人： Jinchao Li , Yu Wang , Karan Srivastava , Jianfeng Gao , Prabhdeep Singh , Haiyuan Cao , Xinying Song , Hui Su , Jaideep Sarkar
摘要： Generally discussed herein are devices, systems, and methods for scheduling tasks to be completed by resources. A method can include identifying features of the task, the features including a time-dependent feature and a time-independent feature, the time-dependent feature indicating a time the task is more likely to be successfully completed by the resource, converting the features to feature values based on a predefined mapping of features to feature values in a first memory device, determining, by a gradient boost tree model and based on a first current time and the feature values, a likelihood the resource will successfully complete the task, and scheduling the task to be performed by the resource based on the determined likelihood.
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公开(公告)号：US10445650B2
公开(公告)日：2019-10-15
申请号：US14949156
申请日：2015-11-23
发明人： Jianfeng Gao , Li Deng , Xiaodong He , Lin Xiao , Xinying Song , Yelong Shen , Ji He , Jianshu Chen
IPC分类号： G06N7/00
摘要： A processing unit can successively operate layers of a multilayer computational graph (MCG) according to a forward computational order to determine a topic value associated with a document based at least in part on content values associated with the document. The processing unit can successively determine, according to a reverse computational order, layer-specific deviation values associated with the layers based at least in part on the topic value, the content values, and a characteristic value associated with the document. The processing unit can determine a model adjustment value based at least in part on the layer-specific deviation values. The processing unit can modify at least one parameter associated with the MCG based at least in part on the model adjustment value. The MCG can be operated to provide a result characteristic value associated with test content values of a test document.
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公开(公告)号：US11068304B2
公开(公告)日：2021-07-20
申请号：US16285170
申请日：2019-02-25
发明人： Jinchao Li , Xinying Song , Ah Young Kim , Haiyuan Cao , Yu Wang , Hui Su , Shahina Ferdous , Jianfeng Gao , Karan Srivastava , Jaideep Sarkar
IPC分类号： G06F9/48 , G06F9/46 , H04M3/52 , H04M3/51 , G06N20/00 , G06Q10/04 , G06Q10/06 , G06Q10/10 , G06F9/50 , G06K9/62 , H04M3/523 , G06N7/00 , G06N3/08 , G06N20/20
摘要： Systems and methods are disclosed for intelligent scheduling of calls to sales leads, leveraging machine learning (ML) to optimize expected results. One exemplary method includes determining, using a connectivity prediction model, call connectivity rate predictions; determining timeslot resources; allocating, based at least on the call connectivity rate predictions and timeslot resources, leads to timeslots in a first time period; determining, within a timeslot and using a lead scoring model, lead prioritization among leads within the timeslot; configuring, based at least on the lead prioritization, the telephone unit with lead information for placing a phone call; and applying a contextual bandit (ML) process to update the connectivity prediction model, the lead scoring model, or both. During subsequent time periods, the updated connectivity prediction and lead scoring models are used, thereby improving expected results over time.
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公开(公告)号：US10579430B2
公开(公告)日：2020-03-03
申请号：US15972968
申请日：2018-05-07
发明人： Xinying Song , Jaideep Sarkar , Karan Srivastava , Jianfeng Gao , Prabhdeep Singh , Hui Su , Jinchao Li , Andreea Bianca Spataru
摘要： Generally discussed herein are devices, systems, and methods for task routing. A method can include receiving, from a resource, a request for a task, in response to receiving the request, determining whether to retrieve a new task of new tasks stored in a first queue or a backlog task of backlog tasks stored in a second queue based on a combined amount of backlog tasks and new tasks relative to a capacity of the resource or the resources, retrieving the new task or the backlog task from the determined first queue or second queue, respectively, based on the determination, and providing the retrieved task to the resource.
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公开(公告)号：US20190303197A1
公开(公告)日：2019-10-03
申请号：US15943206
申请日：2018-04-02
发明人： Jinchao Li , Yu Wang , Karan Srivastava , Jianfeng Gao , Prabhdeep Singh , Haiyuan Cao , Xinying Song , Hui Su , Jaideep Sarkar
摘要： Generally discussed herein are devices, systems, and methods for scheduling tasks to be completed by resources. A method can include identifying features of the task, the features including a time-dependent feature and a time-independent feature, the time-dependent feature indicating a time the task is more likely to be successfully completed by the resource, converting the features to feature values based on a predefined mapping of features to feature values in a first memory device, determining, by a gradient boost tree model and based on a first current time and the feature values, a likelihood the resource will successfully complete the task, and scheduling the task to be performed by the resource based on the determined likelihood.
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公开(公告)号：US10042961B2
公开(公告)日：2018-08-07
申请号：US14811397
申请日：2015-07-28
发明人： Yelong Shen , Xinying Song , Jianfeng Gao , Chenlei Guo , Byungki Byun , Ye-Yi Wang , Brian D. Remick , Edward Thiele , Mohammed Aatif Ali , Marcus Gois , Yang Zou , Mariana Stepp , Divya Jetley , Stephen Friesen
摘要： Techniques for providing a people recommendation system for predicting and recommending relevant people (or other entities) to include in a conversation. In an exemplary embodiment, a plurality of conversation boxes associated with communications between a user and target recipients, or between other users and recipients, are collected and stored as user history. During a training phase, the user history is used to train encoder and decoder blocks in a de-noising auto-encoder model. During a prediction phase, the trained encoder and decoder are used to predict one or more recipients for a current conversation box composed by the user, based on contextual and other signals extracted from the current conversation box. The predicted recipients are ranked using a scoring function, and the top-ranked individuals or entities may be recommended to the user.
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公开(公告)号：US20170147942A1
公开(公告)日：2017-05-25
申请号：US14949156
申请日：2015-11-23
发明人： Jianfeng Gao , Li Deng , Xiaodong He , Lin Xiao , Xinying Song , Yelong Shen , Ji He , Jianshu Chen
IPC分类号： G06N99/00
CPC分类号： G06N7/005
摘要： A processing unit can successively operate layers of a multilayer computational graph (MCG) according to a forward computational order to determine a topic value associated with a document based at least in part on content values associated with the document. The processing unit can successively determine, according to a reverse computational order, layer-specific deviation values associated with the layers based at least in part on the topic value, the content values, and a characteristic value associated with the document. The processing unit can determine a model adjustment value based at least in part on the layer-specific deviation values. The processing unit can modify at least one parameter associated with the MCG based at least in part on the model adjustment value. The MCG can be operated to provide a result characteristic value associated with test content values of a test document.
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公开(公告)号：US20160323398A1
公开(公告)日：2016-11-03
申请号：US14806281
申请日：2015-07-22
发明人： Chenlei Guo , Jianfeng Gao , Xinying Song , Byungki Byun , Yelong Shen , Ye-Yi Wang , Brian D. Remick , Edward Thiele , Mohammed Aatif Ali , Marcus Gois , Xiaodong He , Jianshu Chen , Divya Jetley , Stephen Friesen
CPC分类号： H04L67/22 , G06F17/3053 , G06F17/30699 , G06N99/005 , G06Q10/06311 , G06Q10/06313 , G06Q10/06315 , H04L51/20 , H04L67/306
摘要： Techniques for providing a people recommendation system for predicting and recommending relevant people (or other entities) to include in a conversation based on contextual indicators. In an exemplary embodiment, email recipient recommendations may be suggested based on contextual signals, e.g., project names, body text, existing recipients, current date and time, etc. In an aspect, a plurality of properties including ranked key phrases are associated with profiles corresponding to personal entities. Aggregated profiles are analyzed using first- and second-layer processing techniques. The recommendations may be provided to the user reactively, e.g., in response to a specific query by the user to the people recommendation system, or proactively, e.g., based on the context of what the user is currently working on, in the absence of a specific query by the user.
摘要翻译： 提供人员推荐系统的技术，用于根据情境指标预测和推荐相关人员（或其他实体）包括在对话中。 在示例性实施例中，可以基于上下文信号（例如项目名称，正文，现有收件人，当前日期和时间等）来建议电子邮件接收者建议。在一方面，包括排序关键短语的多个属性与简档相关联 对应个人实体。 使用第一层和第二层处理技术分析聚集的轮廓。 可以例如响应于用户对人们推荐系统的特定查询，或主动地，例如，基于用户当前正在工作的上下文，在没有 由用户进行具体查询。
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公开(公告)号：US20160321283A1
公开(公告)日：2016-11-03
申请号：US14811397
申请日：2015-07-28
发明人： Yelong Shen , Xinying Song , Jianfeng Gao , Chenlei Guo , Byungki Byun , Ye-Yi Wang , Brian D. Remick , Edward Thiele , Mohammed Aatif Ali , Marcus Gois , Yang Zou , Mariana Stepp , Divya Jetley , Stephen Friesen
CPC分类号： G06F17/3097 , G06F17/3053 , G06F17/30598 , G06F17/30699 , G06Q10/06311 , G06Q10/06313 , G06Q10/06315 , H04L51/04
摘要： Techniques for providing a people recommendation system for predicting and recommending relevant people (or other entities) to include in a conversation. In an exemplary embodiment, a plurality of conversation boxes associated with communications between a user and target recipients, or between other users and recipients, are collected and stored as user history. During a training phase, the user history is used to train encoder and decoder blocks in a de-noising auto-encoder model. During a prediction phase, the trained encoder and decoder are used to predict one or more recipients for a current conversation box composed by the user, based on contextual and other signals extracted from the current conversation box. The predicted recipients are ranked using a scoring function, and the top-ranked individuals or entities may be recommended to the user.
摘要翻译： 提供用于预测和推荐相关人（或其他实体）包括在对话中的人推荐系统的技术。 在示例性实施例中，与用户和目标接收者之间或其他用户和接收者之间的通信相关联的多个会话框被收集并存储为用户历史。 在训练阶段，用户历史用于在去噪自动编码器模型中训练编码器和解码器块。 在预测阶段期间，经训练的编码器和解码器用于基于从当前会话框提取的上下文和其他信号来预测用户组成的当前会话框的一个或多个接收者。 使用评分功能对预测的收件者进行排名，并且可以向用户推荐排名最高的个人或实体。
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公开(公告)号：US11734066B2
公开(公告)日：2023-08-22
申请号：US16737474
申请日：2020-01-08
发明人： Jinchao Li , Yu Wang , Karan Srivastava , Jianfeng Gao , Prabhdeep Singh , Haiyuan Cao , Xinying Song , Hui Su , Jaideep Sarkar
CPC分类号： G06F9/4887 , G06F9/4881 , G06F9/5005 , G06F18/21 , G06N20/00
摘要： Generally discussed herein are devices, systems, and methods for scheduling tasks to be completed by resources. A method can include identifying features of the task, the features including a time-dependent feature and a time-independent feature, the time-dependent feature indicating a time the task is more likely to be successfully completed by the resource, converting the features to feature values based on a predefined mapping of features to feature values in a first memory device, determining, by a gradient boost tree model and based on a first current time and the feature values, a likelihood the resource will successfully complete the task, and scheduling the task to be performed by the resource based on the determined likelihood.
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