公开(公告)号：US10061300B1

公开(公告)日：2018-08-28

申请号：US15721208

申请日：2017-09-29

申请人： Xometry, Inc.

发明人： Valerie R. Coffman ,  Mark Wicks ,  Daniel Wheeler

IPC分类号： G06F19/18 ,  G05B19/4097 ,  G06N7/00 ,  G06N3/12 ,  G06N99/00

CPC分类号： G05B19/4097 ,  G05B2219/35134 ,  G05B2219/35204 ,  G06N3/0454 ,  G06N3/126 ,  G06N5/04 ,  G06N7/005 ,  G06N20/00 ,  G06N20/20

摘要： The subject technology is related to methods and apparatus for discretization, manufacturability analysis, and optimization of manufacturing process based on computer assisted design models and machine learning. An apparatus determines from the digital model features of a physical object. Thereafter, the apparatus produces predictive values for manufacturing processes based on regression machine learning models. The apparatus generates a non-deterministic response including a non-empty set of attributes of manufacture processes of the physical object based on a multi-objective optimization model. The non-deterministic response complies or satisfies a selected multi-objective condition included in the multi-objective optimization model.

公开(公告)号：US20180239949A1

公开(公告)日：2018-08-23

申请号：US15553150

申请日：2016-02-23

申请人： CELLANYX DIAGNOSTICS, LLC

发明人： Ashok CHANDER ,  Wendell SU ,  Jonathan VARSANIK

IPC分类号： G06K9/00 ,  G01N33/50 ,  G16H30/40 ,  G01N33/574 ,  G06K9/62 ,  G06F15/18

CPC分类号： G06K9/00127 ,  G01N33/5011 ,  G01N33/502 ,  G01N33/574 ,  G01N2800/50 ,  G01N2800/56 ,  G01N2800/60 ,  G01N2800/7028 ,  G06K9/6256 ,  G06N3/04 ,  G06N3/084 ,  G06N5/003 ,  G06N5/048 ,  G06N7/005 ,  G06N20/00 ,  G06N20/10 ,  G06N20/20 ,  G16H30/40

摘要： Methods, systems, and devices are provided for evaluating the status of cells in a sample involving imaging of cells, transformation of cell images into biophysical metrics, and transformation of the biophysical metrics into prognostic indications on the cellular and subject levels. Automated apparatus, processes, and analyses are provided according to present disclosure.

公开(公告)号：US20180225685A1

公开(公告)日：2018-08-09

申请号：US15426487

申请日：2017-02-07

申请人： LinkedIn Corporation

发明人： Ho jeong Kim

IPC分类号： G06Q30/02 ,  G06Q50/00 ,  G06Q10/06 ,  G06N7/00

CPC分类号： G06Q30/0202 ,  G06N3/0454 ,  G06N5/003 ,  G06N5/022 ,  G06N7/005 ,  G06N20/10 ,  G06N20/20 ,  G06Q10/067 ,  G06Q50/01

摘要： An online social networking system receives a first set of data associated with activities between its members and its competitors. The system uses the first set of data to develop and train propensity models to predict when the members and the competitors are likely to establish a business relationship. The system tests the propensity models to determine a best propensity model and selects that best propensity model. The system receives a second set of data associated with activities between a particular member and particular competitor. The system uses the best propensity model for predicting when the particular member and the particular competitor are likely to establish a business relationship based on the second set of data, and transmits an electronic message to the particular member relating to the business relationship between the particular member and the particular competitor.

公开(公告)号：US20180196796A1

公开(公告)日：2018-07-12

申请号：US15404932

申请日：2017-01-12

申请人： Microsoft Technology Licensing, LLC

发明人： Xianchao Wu

IPC分类号： G06F17/27 ,  H04L12/58 ,  G06F17/24 ,  G06N99/00 ,  G06N7/00 ,  G06N3/00 ,  G06F17/30

CPC分类号： G06F17/279 ,  G06F16/24522 ,  G06F16/9024 ,  G06F17/2775 ,  G06F17/2785 ,  G06F17/2881 ,  G06N3/006 ,  G06N5/022 ,  G06N20/00 ,  G06N20/10 ,  G06N20/20 ,  H04L51/02

摘要： Systems and methods for multiple topic automated chatting are provided. The systems and method provide multiple topic automated (or artificial intelligence) chatting by analyzing user inputs in a conversation to determine a plurality topics, to determine and score features related to the determined topics and different users, and to create a knowledge graph of the determined topics. Based on these determinations, the systems and methods may determine if a reply should be provided and then predict a reply.

公开(公告)号：US20180144042A1

公开(公告)日：2018-05-24

申请号：US15360939

申请日：2016-11-23

申请人： Google Inc.

发明人： Ying Sheng ,  Yifeng Lu ,  Jing Xie ,  Jie Yang ,  Luis Garcia Pueyo ,  Jinan Lou ,  James Wendt

IPC分类号： G06F17/30 ,  G06F17/24 ,  G06N99/00

CPC分类号： G06F16/285 ,  G06F16/93 ,  G06F17/243 ,  G06F17/248 ,  G06N20/00 ,  G06N20/20 ,  G06Q10/10

摘要： Techniques are described herein for automatically generating data extraction templates for structured documents (e.g., B2C emails, invoices, bills, invitations, etc.), and for assigning classifications to those data extraction templates to streamline data extraction from subsequent structured documents. In various implementations, a data extraction template generated from a cluster of structured documents that share fixed content may be identified. Features of the cluster of structured documents may be applied as input to extraction machine learning model(s) trained to provide location(s) of transient field(s) in structured documents, to determine location(s) of transient field(s) in the cluster of structured documents. An association between the data extraction template and the determined transient field location(s) may be stored. Based on the association, data point(s) may be extracted from a given structured document of a user that shares fixed content with the cluster of structured documents. The extracted data point(s) may be surfaced to the user.

公开(公告)号：US20180107787A1

公开(公告)日：2018-04-19

申请号：US15295847

申请日：2016-10-17

申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION

发明人： Colin Compas ,  Yaniv Gur ,  Mehdi Moradi ,  Mohammadreza Negahdar ,  Tanveer Syeda-Mahmood

IPC分类号： G06F19/00 ,  G06Q10/06 ,  G06N3/08

CPC分类号： G16H10/60 ,  G06K9/00 ,  G06K9/0053 ,  G06K9/3266 ,  G06K9/6274 ,  G06K2209/01 ,  G06K2209/05 ,  G06N3/0454 ,  G06N3/08 ,  G06N5/003 ,  G06N20/10 ,  G06N20/20 ,  G06Q10/0633 ,  G16H30/20 ,  G16H50/20

摘要： Workflows for automatic measurement of Doppler is provided. In various embodiments, a plurality of frames of a medical video are read. A mode label indicative of a mode of each of the plurality of frames is determined. At least one of the plurality of frames is provided to a trained feature generator. The at least one of the plurality of frames have the same mode label. At least one feature vector is obtained from the trained feature generator corresponding to the at least one of the plurality of frames. At least one feature vector is provided to a trained classifier. A valve label indicative of a valve is obtained from the trained classifier corresponding to the at least one of the plurality of frames. One or more measurement is extracted indicative of a disease condition from those of the at least one of the plurality of frames matching a predetermined valve label.

公开(公告)号：US20180107645A1

公开(公告)日：2018-04-19

申请号：US15782367

申请日：2017-10-12

申请人： SkywriterRX, Inc.

发明人： Holly Lynn Payne ,  Mark Fielding Bregman ,  Bogart Vargas ,  Thamar Solorio ,  Suraj Maharjan ,  Sudita Kar

IPC分类号： G06F17/27 ,  G06F17/28 ,  G06F17/30 ,  G06F15/18

CPC分类号： G06F17/274 ,  G06F16/24578 ,  G06F16/35 ,  G06F16/383 ,  G06F16/94 ,  G06F16/9535 ,  G06F16/9536 ,  G06F17/2705 ,  G06F17/2735 ,  G06F17/2785 ,  G06F17/2881 ,  G06N3/0454 ,  G06N5/003 ,  G06N5/04 ,  G06N20/00 ,  G06N20/10 ,  G06N20/20 ,  G06Q30/0241 ,  G06Q30/0251 ,  G06Q30/0631

摘要： A method includes generating style values and experiential language tags (ELTs) for a plurality of books based on retrieved book content and reader reviews, respectively. The method further includes generating an ELT prediction model based on the style values and the ELTs. The ELT prediction model is configured to receive a set of style values for a new book and output a set of predicted ELTs for the new book, the set of predicted ELTs indicating predicted reader experiences with the new book. The method further includes receiving user-submitted book content from a remote user device, determining style values for the user-submitted book content, and determining a list of predicted ELTs for the user-submitted book content using the style values for the user-submitted book content and the ELT prediction model. Additionally, the method includes transmitting, to the user device, the list of predicted ELTs for the user-submitted book content.

公开(公告)号：US20180087360A1

公开(公告)日：2018-03-29

申请号：US15276189

申请日：2016-09-26

申请人： International Business Machines Corporation

发明人： Andrew R. Conn ,  Lior Horesh ,  Matthias Kormaksson ,  Moshood O. Saliu ,  Theodore G. van Kessel

IPC分类号： E21B43/24 ,  E21B41/00 ,  G06N3/08 ,  G06N3/04

CPC分类号： E21B43/2406 ,  E21B41/0092 ,  G05B13/0275 ,  G05B13/048 ,  G06N3/0445 ,  G06N3/08 ,  G06N5/003 ,  G06N20/10 ,  G06N20/20

摘要： A method for increasing efficiency in emulsion production for a steam-assisted gravity drainage (SAGD) oil well system includes generating a causal model of the SAGD oil well system and training the causal model of the SAGD oil well system utilizing historical time series data relating to one or more SAGD oil wells at one or more SAGD production sites of the SAGD oil well system. The historical time series data is obtained from a plurality of sensors in the SAGD oil well system. The method also includes utilizing the causal model to determine a forecast emulsion production and a forecast set of control parameters associated with one or more of the SAGD production sites of the SAGD oil well system. The method further includes adjusting a set of controls of the SAGD oil well system based on the forecast emulsion production and the forecast set of control parameters and subject to one or more constraints associated with the SAGD oil well system.

公开(公告)号：US20180082206A1

公开(公告)日：2018-03-22

申请号：US15704899

申请日：2017-09-14

申请人： Foursquare Labs, Inc.

发明人： Stephanie Yang ,  Lauren Hannah ,  Daniel Kronovet ,  Catgatay Berk Kapicioglu

IPC分类号： G06N7/00 ,  G06N99/00

CPC分类号： G06N20/20 ,  G06F16/29 ,  G06N7/005 ,  G06N20/00 ,  G06Q30/0201 ,  H04W4/021 ,  H04W4/38 ,  Y02D70/00 ,  Y02D70/10 ,  Y02D70/14 ,  Y02D70/142 ,  Y02D70/144 ,  Y02D70/164 ,  Y02D70/166

摘要： Examples of the present disclosure describe systems and methods for passive visit detection. In aspects, a mobile device comprising a set of sensors may collect and store sensor data from the set of sensors in response to detecting a movement event or user interaction data. The collected sensor data may be processed and provided as input to one or more predictive or statistical models. The model(s) may evaluate the sensor data to detect mobile device location, movement events and visit events. The model(s) may also be used to determine correlations between features of the sensor data and movement- or location-based events, optimize the types of data collected by the set of sensors, extend localized predictions to large-scale ecosystems, and generate battery-efficient state predictions. In aspects, the model(s) may be trained using labeled and/or unlabeled data sets of sensor data.

公开(公告)号：US20180063265A1

公开(公告)日：2018-03-01

申请号：US15691410

申请日：2017-08-30

申请人： ORACLE INTERNATIONAL CORPORATION

发明人： Peter Crossley ,  Ethan Dereszynski

IPC分类号： H04L29/08 ,  G06N99/00 ,  G06N7/00

CPC分类号： H04L67/22 ,  G06N3/02 ,  G06N5/003 ,  G06N7/005 ,  G06N20/00 ,  G06N20/10 ,  G06N20/20 ,  H04L67/02 ,  H04L67/306

摘要： Methods and systems are provided for processing tag-based event communications using machine learning. One or more event communications are received from a user device. The communication(s) include key-value pairs representing an ordered sequence of multiple interaction events of a set of predefined events. Each communication of the one or more event communications includes one generated via execution of tag code integrated with code of an app page or of a webpage. A representation of the ordered sequence is processed using a machine learning model to generate one or more profile estimation results that include an identification of a particular user profile from amongst a set of stored user profile. Profile data is transmitted to a client system that identifies the particular user profile or is from the particular user profile.