CO2023016153A2 - Sistema y método para afinar el análisis automatizado de sentimiento - Google Patents
Sistema y método para afinar el análisis automatizado de sentimientoInfo
- 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
Links
- 238000000034 method Methods 0.000 title abstract 2
- 238000010801 machine learning Methods 0.000 abstract 6
Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/30—Semantic analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/211—Selection of the most significant subset of features
- G06F18/2113—Selection 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/217—Validation; Performance evaluation; Active pattern learning techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/243—Classification techniques relating to the number of classes
- G06F18/2431—Multiple classes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/40—Software arrangements specially adapted for pattern recognition, e.g. user interfaces or toolboxes therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
- G06N20/20—Ensemble 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.
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)
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 |
-
2021
- 2021-05-12 EP EP21733599.1A patent/EP4338090A1/en active Pending
- 2021-05-12 AU AU2021445464A patent/AU2021445464A1/en active Pending
- 2021-05-12 WO PCT/US2021/031991 patent/WO2022240404A1/en active Application Filing
- 2021-05-12 JP JP2023568669A patent/JP2024521041A/ja active Pending
- 2021-05-12 US US17/318,467 patent/US20220366197A1/en active Pending
- 2021-05-12 CA CA3218840A patent/CA3218840A1/en active Pending
- 2021-05-12 CN CN202180098675.2A patent/CN117396881A/zh active Pending
- 2021-05-12 BR BR112023023460A patent/BR112023023460A2/pt unknown
-
2023
- 2023-11-29 CO CONC2023/0016153A patent/CO2023016153A2/es unknown
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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