- Primeros pasos
- Componentes de marco
- Resumen de la clasificación de documentos
- Asistente para Configurar clasificadores de Clasificar ámbito de documento
- Clasificador basado en palabras clave
- Clasificador inteligente de palabra clave
- Clasificador de CapturaFlexible
- Clasificador de aprendizaje automático
- Actividades relacionadas con la clasificación de documentos
- Resumen de la extracción de datos
- Asistente para Configurar extractores del ámbito de extracción de datos
- Extractor basado en regex
- Extractor de forma
- Extractor inteligente de formularios
- Extractor con aprendizaje automático
- Extractor CapturaFlexible
- Actividades relacionadas con la extracción de datos
- Paquetes ML
- Procesos
- Gestor de datos
- Servicios de OCR
- Document Understanding implementado en Automation Suite
- Document Understanding implementado en AI Center independiente
- Aprendizaje profundo
- Licencia
- Referencias
- Actividades.DeUipath
- UiPath.AbbyyEmbedded.Activities
- UiPath.DocumentUnderstanding.ML.Activities
- UiPath.DocumentUnderstanding.OCR.LocalServer.Activities
- UiPath.IntelligentOCR.Activities
- UiPath.OCR.Activities
- UiPath.OCR.Contracts
- UiPath.DocumentProcessing.Contracts
- UiPath.OmniPage.Activities
- UiPath.PDF.Activities
El asistente para Configurar extractores, al que se accede a través de Ámbito de extracción de datos, permite elegir qué extractores se aplican a cada tipo de documento y campo.
It can be opened from the body of the activity, by clicking on the Configure Extractors button. The wizard button becomes available after dragging at least one extractor activity into the body of the Data Extraction Scope activity. This wizard displays all the document types defined in the taxonomy and their respective fields and enables you to choose which extractor you want to use for each.
Cada tipo de documento puede ampliarse y sus campos pueden visualizarse en el asistente y seleccionarse para la extracción.
The Framework Alias field can be used to map an extractor to one or more trainers. For instance, you can give a Machine Learning Extractor the alias R2D2 and then you can use the same alias for a Machine Learning Extractor Trainer. This creates a link between the extractor and the trainer and has training purposes for the extractor. Each extractor has a unique alias while multiple trainers can share the same alias.
The Minimum Confidence field can be configured with a value between 0 and 100 and represents the confidence threshold above which extracted data is taken into account. If a result of a selected field has a confidence level below the confidence threshold, it is not reported in the final result.
The Get of refresh extractor capabilities button, for the extractors that support this functionality, can be used to easily map your taxonomy fields with the available extractor fields or refresh them in case the extractor fields have changed.
The checkboxes next to each field in any column, if selected, cause the extractor to be asked for a value for the specified field. If cleared, the field is ignored when extracting data.
The text fields next to each document field enable you to map fields defined in your Taxonomy with the fields defined in the extractor's internal taxonomy if any.
El número de columnas del asistente varía en función del número de extractores presentes en la actividad de ámbito. El nombre de cada columna viene dado por el nombre para mostrar de cada actividad de extractor.
If multiple extractors are used in the activity, the order of the extractors in the scope defines their priority. For example, in the image above, if Extractor 1 returns an acceptable value (which is above the Minimum Confidence level) for a particular requested field, then that field is not requested when Extractor 2 and Extractor 3 are executed. If Extractor 1 and Extractor 2 return values below the Minimum Confidence level for that particular field, or return nothing at all, the results from Extractor 3 are taken into account, if they satisfy the confidence acceptability conditions.