MX364165B - Métodos y sistemas para la busqueda de patrones lógicos. - Google Patents

Métodos y sistemas para la busqueda de patrones lógicos.

Info

Publication number
MX364165B
MX364165B MX2016003370A MX2016003370A MX364165B MX 364165 B MX364165 B MX 364165B MX 2016003370 A MX2016003370 A MX 2016003370A MX 2016003370 A MX2016003370 A MX 2016003370A MX 364165 B MX364165 B MX 364165B
Authority
MX
Mexico
Prior art keywords
patterns
logical
sequence
sensor
searching
Prior art date
Application number
MX2016003370A
Other languages
English (en)
Other versions
MX2016003370A (es
Inventor
Agarwal Puneet
Shroff Gautam
Srinivasan Ashwin
Hassan Ehtesham
Yadav Mohit
Original Assignee
Tata Consultancy Services Ltd
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 Tata Consultancy Services Ltd filed Critical Tata Consultancy Services Ltd
Publication of MX2016003370A publication Critical patent/MX2016003370A/es
Publication of MX364165B publication Critical patent/MX364165B/es

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/951—Indexing; Web crawling techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10—File systems; File servers
    • G06F16/14—Details of searching files based on file metadata
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2457—Query processing with adaptation to user needs
    • G06F16/24573—Query processing with adaptation to user needs using data annotations, e.g. user-defined metadata
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2457—Query processing with adaptation to user needs
    • G06F16/24578—Query processing with adaptation to user needs using ranking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
    • G06F16/2477—Temporal data queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28—Databases characterised by their database models, e.g. relational or object models
    • G06F16/284—Relational databases
    • G06F16/285—Clustering or classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • 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
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • G06V20/54—Surveillance or monitoring of activities, e.g. for recognising suspicious objects of traffic, e.g. cars on the road, trains or boats
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
    • G06F2218/12—Classification; Matching
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/04—Manufacturing

Abstract

Se proporcionan métodos y sistemas para buscar patrones lógicos en datos de múltiples sensores voluminosos desde la internet industrial. El método recupera instancias de patrones en datos de series de tiempo donde los patrones se especifican lógicamente, usando una secuencia de símbolos. Los símbolos lógicos usados son un subconjunto de las abstracciones cualitativas específicamente, los conceptos de fijo, creciente, decreciente. Los patrones pueden incluir secuencias de símbolos para múltiples sensores, duración aproximada así como valores de pendiente para cada símbolo. Para facilitar la consulta eficaz, cada serie de tiempo de sensor se preprocesa en una secuencia de símbolos lógicos. Cada posición en la secuencia comprimida resultante se registra a través de una estructura de índice basada en TRIE que corresponde a los múltiples patrones lógicos a los que puede pertenecer. Los patrones de múltiples sensores lógicos se recuperan y clasifican de manera eficaz usando una estructura de este tipo. Este método para indexar y buscar proporciona un mecanismo eficaz para análisis exploratorio de datos de múltiples sensores voluminosos.
MX2016003370A 2015-06-19 2016-03-15 Métodos y sistemas para la busqueda de patrones lógicos. MX364165B (es)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
IN2351MU2015 2015-06-19

Publications (2)

Publication Number Publication Date
MX2016003370A MX2016003370A (es) 2017-01-18
MX364165B true MX364165B (es) 2019-04-15

Family

ID=56134235

Family Applications (1)

Application Number Title Priority Date Filing Date
MX2016003370A MX364165B (es) 2015-06-19 2016-03-15 Métodos y sistemas para la busqueda de patrones lógicos.

Country Status (7)

Country Link
US (1) US9996617B2 (es)
EP (1) EP3107036A1 (es)
JP (1) JP6807649B2 (es)
AU (1) AU2016201689B2 (es)
BR (1) BR102016005928A2 (es)
CA (1) CA2923908C (es)
MX (1) MX364165B (es)

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EP3537338B1 (en) * 2018-03-07 2021-11-03 Tata Consultancy Services Limited Method and system for pattern recognition in a signal using morphology aware symbolic representation
US11022511B2 (en) 2018-04-18 2021-06-01 Aron Kain Sensor commonality platform using multi-discipline adaptable sensors for customizable applications
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US10831631B2 (en) * 2018-06-28 2020-11-10 International Business Machines Corporation Continuous time alignment of a collection of independent sensors
CN109784380A (zh) * 2018-12-27 2019-05-21 西安交通大学 一种基于生成对抗学习的多维度田间杂草识别方法
JP7010861B2 (ja) * 2019-02-07 2022-01-26 ファナック株式会社 状態判定装置及び状態判定方法
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US11321406B2 (en) 2019-07-31 2022-05-03 Walmart Apollo, Llc Personalized ranking using deep attribute extraction and attentive user interest embeddings
US20210034945A1 (en) * 2019-07-31 2021-02-04 Walmart Apollo, Llc Personalized complimentary item recommendations using sequential and triplet neural architecture
US11500932B2 (en) * 2020-05-19 2022-11-15 International Business Machines Corporation Change-point driven feature selection for multi-variate time series clustering
DE102021130938A1 (de) 2021-11-25 2023-05-25 Dr. Ing. H.C. F. Porsche Aktiengesellschaft Verfahren, System und Computerprogrammprodukt zur Analyse von Zeitreihendatensätzen einer Entität

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JP3204154B2 (ja) * 1997-02-21 2001-09-04 日本電気株式会社 時系列データ解析装置
US6766316B2 (en) * 2001-01-18 2004-07-20 Science Applications International Corporation Method and system of ranking and clustering for document indexing and retrieval
US8407164B2 (en) * 2006-10-02 2013-03-26 The Trustees Of Columbia University In The City Of New York Data classification and hierarchical clustering
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Also Published As

Publication number Publication date
CA2923908C (en) 2023-08-29
US9996617B2 (en) 2018-06-12
US20160371376A1 (en) 2016-12-22
JP2017010523A (ja) 2017-01-12
AU2016201689A1 (en) 2017-01-12
JP6807649B2 (ja) 2021-01-06
AU2016201689B2 (en) 2017-11-23
EP3107036A1 (en) 2016-12-21
BR102016005928A2 (pt) 2016-12-27
CA2923908A1 (en) 2016-12-19
MX2016003370A (es) 2017-01-18

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