CO2019011810A2 - Guía de toma de decisiones mediante aprendizaje automático para alertas originarias de sistemas de monitorización - Google Patents

Guía de toma de decisiones mediante aprendizaje automático para alertas originarias de sistemas de monitorización

Info

Publication number
CO2019011810A2
CO2019011810A2 CONC2019/0011810A CO2019011810A CO2019011810A2 CO 2019011810 A2 CO2019011810 A2 CO 2019011810A2 CO 2019011810 A CO2019011810 A CO 2019011810A CO 2019011810 A2 CO2019011810 A2 CO 2019011810A2
Authority
CO
Colombia
Prior art keywords
error
decision
machine learning
monitoring systems
determined
Prior art date
Application number
CONC2019/0011810A
Other languages
English (en)
Inventor
Vidar V Vikjord
Jan-Ove Karlberg
Original Assignee
Microsoft Technology Licensing Llc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Microsoft Technology Licensing Llc filed Critical Microsoft Technology Licensing Llc
Publication of CO2019011810A2 publication Critical patent/CO2019011810A2/es

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
    • G06F11/079—Root cause analysis, i.e. error or fault diagnosis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/36—Preventing errors by testing or debugging software
    • G06F11/362—Software debugging
    • G06F11/366—Software debugging using diagnostics
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
    • G06F11/0703—Error or fault processing not based on redundancy, i.e. by taking additional measures to deal with the error or fault not making use of redundancy in operation, in hardware, or in data representation
    • G06F11/0793—Remedial or corrective actions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F11/00—Error detection; Error correction; Monitoring
    • G06F11/36—Preventing errors by testing or debugging software
    • G06F11/362—Software debugging
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/04—Inference or reasoning models
    • G06N5/045—Explanation of inference; Explainable artificial intelligence [XAI]; Interpretable artificial intelligence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computing arrangements based on specific mathematical models
    • G06N7/01—Probabilistic graphical models, e.g. probabilistic networks

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Software Systems (AREA)
  • Quality & Reliability (AREA)
  • Data Mining & Analysis (AREA)
  • Mathematical Physics (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Computing Systems (AREA)
  • Computer Hardware Design (AREA)
  • Medical Informatics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Computational Linguistics (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Probability & Statistics with Applications (AREA)
  • Algebra (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Debugging And Monitoring (AREA)
  • Stored Programmes (AREA)
  • Train Traffic Observation, Control, And Security (AREA)
  • Alarm Systems (AREA)
  • Facsimiles In General (AREA)
  • Display Devices Of Pinball Game Machines (AREA)
  • Computer And Data Communications (AREA)
  • Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)

Abstract

En el presente documento se describe un sistema y un método para determinar si un problema detectado en un sistema de cómputo es un error introducido por un desarrollador o un problema intermitente. Cuando se detecta un problema, se recibe información sobre el problema. Entonces se determina si el problema es nuevo o si se detectó previamente. Cuando se determina que el problema es nuevo, la información sobre el problema se almacena en un dispositivo de almacenamiento. Se genera un vector de características para el problema y se analiza para determinar la probabilidad de que el problema sea un error. Cuando se determina que el problema es un error, la ocurrencia del problema se informa a un usuario del sistema que puede corregir el error. Una vez que se corrige el error, la corrección se devuelve al sistema y se utiliza para entrenar el sistema.
CONC2019/0011810A 2017-04-24 2019-10-24 Guía de toma de decisiones mediante aprendizaje automático para alertas originarias de sistemas de monitorización CO2019011810A2 (es)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US15/495,255 US10482000B2 (en) 2017-04-24 2017-04-24 Machine learned decision guidance for alerts originating from monitoring systems
PCT/US2018/026380 WO2018200154A1 (en) 2017-04-24 2018-04-06 Machine learned decision guidance for alerts originating from monitoring systems

Publications (1)

Publication Number Publication Date
CO2019011810A2 true CO2019011810A2 (es) 2020-01-17

Family

ID=62111185

Family Applications (1)

Application Number Title Priority Date Filing Date
CONC2019/0011810A CO2019011810A2 (es) 2017-04-24 2019-10-24 Guía de toma de decisiones mediante aprendizaje automático para alertas originarias de sistemas de monitorización

Country Status (17)

Country Link
US (2) US10482000B2 (es)
EP (1) EP3616065A1 (es)
JP (1) JP2020518064A (es)
KR (1) KR102589649B1 (es)
CN (2) CN117112281A (es)
AU (2) AU2018257811B2 (es)
BR (1) BR112019019922A2 (es)
CA (1) CA3056948A1 (es)
CL (1) CL2019002924A1 (es)
CO (1) CO2019011810A2 (es)
IL (1) IL270079B2 (es)
MX (1) MX2019012625A (es)
PH (1) PH12019550190A1 (es)
RU (1) RU2767143C2 (es)
SG (1) SG11201909410VA (es)
WO (1) WO2018200154A1 (es)
ZA (1) ZA201905871B (es)

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Also Published As

Publication number Publication date
AU2018257811A1 (en) 2019-09-19
AU2018257811B2 (en) 2022-03-10
IL270079B2 (en) 2023-09-01
MX2019012625A (es) 2020-01-30
JP2020518064A (ja) 2020-06-18
PH12019550190A1 (en) 2020-06-29
US11809304B2 (en) 2023-11-07
KR20200002843A (ko) 2020-01-08
CN110546619B (zh) 2023-09-12
CL2019002924A1 (es) 2020-03-13
IL270079A (es) 2019-12-31
RU2019137600A3 (es) 2021-09-15
US20200050532A1 (en) 2020-02-13
CA3056948A1 (en) 2018-11-01
BR112019019922A2 (pt) 2020-04-22
IL270079B1 (en) 2023-05-01
WO2018200154A1 (en) 2018-11-01
CN117112281A (zh) 2023-11-24
US10482000B2 (en) 2019-11-19
SG11201909410VA (en) 2019-11-28
KR102589649B1 (ko) 2023-10-13
RU2019137600A (ru) 2021-05-25
CN110546619A (zh) 2019-12-06
AU2022203688A1 (en) 2022-06-16
EP3616065A1 (en) 2020-03-04
AU2022203688B2 (en) 2024-02-15
ZA201905871B (en) 2020-11-25
RU2767143C2 (ru) 2022-03-16
US20180307582A1 (en) 2018-10-25

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