CO2023016153A2 - Sistema y método para afinar el análisis automatizado de sentimiento - Google Patents

Sistema y método para afinar el análisis automatizado de sentimiento

Info

Publication number
CO2023016153A2
CO2023016153A2 CONC2023/0016153A CO2023016153A CO2023016153A2 CO 2023016153 A2 CO2023016153 A2 CO 2023016153A2 CO 2023016153 A CO2023016153 A CO 2023016153A CO 2023016153 A2 CO2023016153 A2 CO 2023016153A2
Authority
CO
Colombia
Prior art keywords
model
annotated
fine
sentiment analysis
automated sentiment
Prior art date
Application number
CONC2023/0016153A
Other languages
English (en)
Inventor
Avraham Faizakof
Arnon Mazza
Lev Haikin
Eyal Orbach
Original Assignee
Genesys Cloud Services Inc
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 Genesys Cloud Services Inc filed Critical Genesys Cloud Services Inc
Publication of CO2023016153A2 publication Critical patent/CO2023016153A2/es

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/24Classification techniques
    • G06F18/241Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00Handling natural language data
    • G06F40/30Semantic analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/21Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/211Selection of the most significant subset of features
    • G06F18/2113Selection of the most significant subset of features by ranking or filtering the set of features, e.g. using a measure of variance or of feature cross-correlation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/21Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/217Validation; Performance evaluation; Active pattern learning techniques
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/20Analysing
    • G06F18/24Classification techniques
    • G06F18/243Classification techniques relating to the number of classes
    • G06F18/2431Multiple classes
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00Pattern recognition
    • G06F18/40Software arrangements specially adapted for pattern recognition, e.g. user interfaces or toolboxes therefor
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00Machine learning
    • G06N20/20Ensemble learning

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Evolutionary Biology (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Medical Informatics (AREA)
  • Mathematical Physics (AREA)
  • Computational Linguistics (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Human Computer Interaction (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Machine Translation (AREA)
  • Investigating Or Analysing Biological Materials (AREA)

Abstract

RESUMEN Un método y sistema para afinar la clasificación automatizada de sentimiento mediante al menos un procesador puede incluir: recibir un primer modelo de aprendizaje automático (ML) M0, preentrenado para realizar la clasificación automatizada de sentimiento de enunciados, basado en un primer conjunto de datos de entrenamiento anotados; asociar una o más instancias del modelo M0 a uno o más sitios correspondientes; y para una o más (p. ej., cada) instancias y/o sitios del modelo de ML M0: recibir al menos un enunciado a través del sitio correspondiente; obtener al menos un elemento de datos de retroalimentación anotada, correspondiente a el al menos un enunciado; reentrenar el modelo de ML M0, para producir un segundo modelo de ML M1, basado en un segundo conjunto de datos de entrenamiento anotados, en donde el segundo conjunto de datos de entrenamiento anotados puede incluir el primer conjunto de datos de entrenamiento anotados y el al menos un elemento de datos de retroalimentación anotada; y usar el segundo modelo de ML M1, para clasificar los enunciados de acuerdo con una o más clases de sentimiento.
CONC2023/0016153A 2021-05-12 2023-11-29 Sistema y método para afinar el análisis automatizado de sentimiento CO2023016153A2 (es)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US17/318,467 US20220366197A1 (en) 2021-05-12 2021-05-12 System and method for finetuning automated sentiment analysis
PCT/US2021/031991 WO2022240404A1 (en) 2021-05-12 2021-05-12 System and method for finetuning automated sentiment analysis

Publications (1)

Publication Number Publication Date
CO2023016153A2 true CO2023016153A2 (es) 2024-02-15

Family

ID=76523437

Family Applications (1)

Application Number Title Priority Date Filing Date
CONC2023/0016153A CO2023016153A2 (es) 2021-05-12 2023-11-29 Sistema y método para afinar el análisis automatizado de sentimiento

Country Status (9)

Country Link
US (1) US20220366197A1 (es)
EP (1) EP4338090A1 (es)
JP (1) JP2024521041A (es)
CN (1) CN117396881A (es)
AU (1) AU2021445464A1 (es)
BR (1) BR112023023460A2 (es)
CA (1) CA3218840A1 (es)
CO (1) CO2023016153A2 (es)
WO (1) WO2022240404A1 (es)

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9336202B2 (en) * 2012-05-15 2016-05-10 Whyz Technologies Limited Method and system relating to salient content extraction for electronic content
US9978362B2 (en) * 2014-09-02 2018-05-22 Microsoft Technology Licensing, Llc Facet recommendations from sentiment-bearing content
US20160189037A1 (en) * 2014-12-24 2016-06-30 Intel Corporation Hybrid technique for sentiment analysis

Also Published As

Publication number Publication date
BR112023023460A2 (pt) 2024-01-30
CA3218840A1 (en) 2022-11-17
AU2021445464A1 (en) 2023-11-09
EP4338090A1 (en) 2024-03-20
CN117396881A (zh) 2024-01-12
US20220366197A1 (en) 2022-11-17
WO2022240404A1 (en) 2022-11-17
JP2024521041A (ja) 2024-05-28

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