Other

Microsoft Technology Licensing, LLC

Ge Inspection Technologies, Gmbh

Haiming Zhao

Arun Karthi Subramaniyan

Chi-Yi Kuan

Fabio Nonato De Paula

Xiaosu Huang

Ziliang Lin

Xuan Zhu

Michael Kennedy

Zhengjie Xu

Imran Younus

A method includes receiving a first time-dependent data characterizing measurement by a first sensor operatively coupled to an oil and gas industrial machine; determining a first anomaly score associated with a first portion of the first time-dependent data over a time period, the determination is based on a first value of an operating characteristic over the time period and a second value of the operating characteristic over the time period, wherein the first value of the operating characteristic is calculated from the first time-dependent data and the second value of the operating characteristic is detected at the oil and gas industrial machine; and rendering, in a graphical user interface display space, a visual representation indicative of the first anomaly score. Related apparatus, systems, articles, and techniques are also described.

Anomaly detection

Systems, methods, and a computer readable medium are provided for generating natural language recommendations based on an industrial language model. Input data, including a plurality of natural language input units is received from a first computing device and transmitted to a second computing device. The second computing device can determine an output including a plurality of natural language outputs using a predictive model trained to generate the output corresponding to an energy exploration lexicon. The second computing device can provide the output to the first computing device for display.

Generating natural language recommendations based on an industrial language model

A phony profiles detector for an on-line social network system is described. The phony profiles detector uses characteristics of a profile that was associated with an indication that it represents a malicious user, a so-called seed profile, to identify other profiles that should be flagged as potentially the source of undesirable behavior. Based on the degree of similarity determined for a subject profile with respect to a seed profile, the phony profiles detector generates a malicious user indicator and stores it as associated with the subject profile.

Phony profiles detector

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San Ramon, CA, United States of America

Haiming Zhao