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71. 发明申请

US20200160373A1 OPTIMIZING AND PREDICTING CAMPAIGN ATTRIBUTES 审中-公开
公开(公告)号：US20200160373A1
公开(公告)日：2020-05-21
申请号：US16194973
申请日：2018-11-19
申请人： ToneDen
发明人： Tim THIMMAIAH , Nick ELSBREE , Jake RUSH
IPC分类号： G06Q30/02 , G06N99/00
摘要： Approaches provide for or automatically optimizing sponsored content campaigns for a sponsored content provider for a particular consumption category across different content publisher networks. For example, performance data for sponsored content campaigns can be used to train a model for a consumption category to determine allocation scores that quantify a relationship between target audiences and the consumption category. In response to a content placement request to initiate a sponsored content campaign associated with the consumption category, allocation scores can be determined and used to dynamically determine an allocation of resources to appropriate audiences or segments based at least in part upon the trained optimization model. A campaign template can be generated that includes the target audience(s), sponsored content, and respective budget allocation, and any other information for the campaign. The campaign can proceed based at least in part on the campaign template, and performance of the campaign can be monitored and analyzed during the campaign to optimize the campaign dynamically.

72. 发明申请

US20200160229A1 Creating User Experiences with Behavioral Information and Machine Learning 审中-公开
公开(公告)号：US20200160229A1
公开(公告)日：2020-05-21
申请号：US16192164
申请日：2018-11-15
申请人： Adobe Inc.
发明人： Edmund Francis Anthony Atcheson
IPC分类号： G06N99/00 , G06N5/02
摘要： Automatic user experience generation is described. A user experience system receives input specifying at least one machine learning model to use in generating a user experience for at least one specified user profile. Available machine learning models are identified and displayed for selection by the system based on profile information associated with the user profile(s). An output is generated by applying at least a subset of the profile information as input to the selected machine learning model, and supplies the generated output to at least one different machine learning model, to generate a target outcome for the selected user profile(s). Additionally, the system automatically detects acceptable data input types and formats for a model and translates data as necessary before input to the model(s). Model outputs are then used by an experience generation module to identify digital content corresponding to the outputs and generate user experiences including the digital content.

73. 发明申请

US20200160147A1 HUMAN BRAIN LIKE INTELLIGENT DECISION-MAKING MACHINE 审中-公开
公开(公告)号：US20200160147A1
公开(公告)日：2020-05-21
申请号：US16635892
申请日：2018-08-02
申请人： NATIONAL INSTITUTE FOR MATERIALS SCIENCE
发明人： Anirban BANDYOPADHYAY , Subrata GHOSH , Daisuke FUJITA
IPC分类号： G06N3/04 , G06N10/00 , G06N3/08 , G06N99/00
摘要： Artificial intelligence research is failing to produce true intelligence in spite of enormous resources. The reason is that programming is unavoidable for data processing and so there is no way to replace an user. In addition, because of data deluge problem, it is impossible to analyze all data as conventional information. Hardware inspired by prime metric is provided, where a metric of artificial intelligence is built in which unknown random events are linked as a changing geometric shape. All information is converted such that layered geometric shapes clocking in a pattern or event becomes unit of information, not insignificant bits. All complex events are considered as a single point to go ahead on building higher level geometric shapes as part of a time crystal following prime metric.

74. 发明申请

US20200159995A1 INTELLIGENT COMMUNICATION MESSAGE COMPLETION 审中-公开
公开(公告)号：US20200159995A1
公开(公告)日：2020-05-21
申请号：US16193575
申请日：2018-11-16
申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION
发明人： Maharaj MUKHERJEE , Jonathan LECHNER , Lisa Seacat DELUCA
IPC分类号： G06F40/30 , G06N99/00 , H04L12/58
摘要： Embodiments are provided for intelligent communication message completion in a computing system by a processor. A plurality of contextual factors associated with a communication dialog may be determined and learned. A communication message may be automatically completed according to the plurality of contextual factors associated with the communication dialog.

75. 发明申请

US20200159195A1 SELECTIVE DATA FEEDBACK FOR INDUSTRIAL EDGE SYSTEM 审中-公开
公开(公告)号：US20200159195A1
公开(公告)日：2020-05-21
申请号：US16192968
申请日：2018-11-16
申请人： General Electric Company
发明人： Xiao BIAN , Colin PARRIS , Dayu HUANG , Huan TAN , Kiersten RALSTON , Shaopeng LIU , Guiju SONG
IPC分类号： G05B19/418 , G06N99/00
摘要： The example embodiments are directed to a system and method for optimizing data the is transmitted from an edge device to a central server such as the cloud platform. In one example, the method may include one or more of receiving incoming data which is associated with an industrial asset positioned at an edge of an Internet of Things (IoT) network, transforming the incoming data into a pattern of data points within a feature space based on a machine learning model configured to detect patterns within the data, selecting a subset of data points from the pattern based on a distance between data points in the pattern of data points with respect to a previous pattern of data points in a previous dataset associated with the industrial asset, and transmitting the selected subset of data points to a central platform via the IoT network.

76. 发明申请

US20200156654A1 DUAL-TEST OPERATOR ASSESSMENT 审中-公开
公开(公告)号：US20200156654A1
公开(公告)日：2020-05-21
申请号：US16193079
申请日：2018-11-16
申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION
发明人： Gregory J. Boss , Michael Bender , Jeremy R. Fox , Manjari Roy
IPC分类号： B60W50/14 , G06N99/00 , B60Q9/00 , G05D1/00 , B60W30/09 , A61B5/12 , A61B5/16 , A61B5/18
摘要： In response to determining that performance data of device operation by an operating user meets a safety requirement, embodiments determine a degree of deviation of a performance data value from a baseline pattern of good performance values defined for the user; in response to determining that the degree of deviation of the operating data value meets a cognitive assessment threshold, administer a cognitive aptitude test challenge to the user selected from baseline aptitude profile data of challenges previously responded to by the user; and execute a corrective action that reduces a risk of loss in response to determining that a degree of deviation of a value of a response provided by the user to the cognitive test challenge from a performance metric value of the baseline aptitude profile data meets a threshold cognitive assessment threshold.

77. 发明申请

US20200152326A1 BLOOD PATHOLOGY IMAGE ANALYSIS AND DIAGNOSIS USING MACHINE LEARNING AND DATA ANALYTICS 审中-公开
公开(公告)号：US20200152326A1
公开(公告)日：2020-05-14
申请号：US16185701
申请日：2018-11-09
申请人： International Business Machines Corporation
发明人： Marta Sanchez-Martin , Claudia S. Huettner , Jia Xu , Cheryl Eifert , Elinor Dehan , Shang Xue , Vanessa Michelini
IPC分类号： G16H50/20 , G06N99/00
摘要： Methods, systems, and computer readable media are provided for processing microscopic images of a biological sample from a patient. One or more images of a blood sample from a microscope is obtained, each image comprising a plurality of different types of cells. The one or more images are processed by a machine learning system to classify individual cells into one of a plurality of cell categories. The cells in each cell category are analyzed to determine characteristics of the respective cell category. A diagnosis or list of possible diagnosis are determined based on the classification and characteristics of the cells for the patient in an automated manner.

78. 发明申请

US20200151672A1 RANKING JOB RECOMMENDATIONS BASED ON TITLE PREFERENCES 审中-公开
公开(公告)号：US20200151672A1
公开(公告)日：2020-05-14
申请号：US16185262
申请日：2018-11-09
申请人： Microsoft Technology Licensing, LLC
发明人： Huichao Xue , Ye Yuan , Girish Kathalagiri Somashekariah , Ada Cheuk Ying Yu
IPC分类号： G06Q10/10 , G06Q50/00 , G06N99/00 , G06N5/04
摘要： The disclosed embodiments provide a system that ranks job recommendations based on title preferences. During operation, the system determines features related to applications for jobs by a candidate, wherein the features include a title preference for the candidate and a similarity between a first set of attribute values for the candidate and a second set of attribute values for a job. Next, the system applies a machine learning model to the features to produce scores representing likelihoods of the candidate applying to the jobs. The system then generates a ranking of the jobs by the scores. Finally, the system outputs, to the candidate, at least a portion of the ranking as a set of recommendations.

79. 发明申请

US20200151620A1 MISTAKEN MESSAGE PREVENTION BASED ON MULTIPLE CLASSIFICATION LAYERS 审中-公开
公开(公告)号：US20200151620A1
公开(公告)日：2020-05-14
申请号：US16186626
申请日：2018-11-12
申请人： International Business Machines Corporation
发明人： Tzu-Chen Chao , Ching-Chun Liu , Ci-Wei Lan , Tao-Hung Jung , Yu-Siang Chen
IPC分类号： G06N99/00 , H04L12/58 , G06N7/00
摘要： In an approach to detecting the transmission of messages, analyzing said messages, calculating a message risk score and transmitting a warning notification, one or more computer processors detect transmission of a message from a user to a selected recipient. The one or more computer processors extract message information from the detected message. The one or more computer processors retrieve one or more historical conversations between the user and the selected recipient of the detected message. The one or more computer processors determine a risk score corresponding to sending the detected message to the selected recipient based on applying the extracted message information and the retrieved historical conversations to a cognitive model.

80. 发明申请

US20200151588A1 DECLARATIVE DEBRIEFING FOR PREDICTIVE PIPELINE 审中-公开
公开(公告)号：US20200151588A1
公开(公告)日：2020-05-14
申请号：US16190518
申请日：2018-11-14
申请人： SAP SE
发明人： Jacques DOAN HUU
IPC分类号： G06N5/04 , G06N99/00
摘要： Provided are systems and methods for auto-completing debriefing processing for a machine learning model pipeline based on a type of predictive algorithm. In one example, the method may include one or more of building a machine learning model pipeline via a user interface, detecting, via the user interface, a selection associated with a predictive algorithm included within the machine learning model pipeline, in response to the selection, identifying debriefing components for the predictive algorithm based on a type of the predictive algorithm from among a plurality of types of predictive algorithms, and automatically incorporating processing for the debriefing components within the machine learning model pipeline such that values of the debriefing components are generated during training of the predictive algorithm within the machine learning model pipeline.

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