Document Processing with Deep Learning
Abstract
All companies have a large number of documents in free text format where useful data is stored for them. Extracting information from various documents that have a certain structure is relatively easy using the appropriate tools, because the structure itself tells us where certain data can be located. When the documents in question do not have a structure, or even worse, when the structure changes for the same type of document from one region to another, or even within the same region, more complex techniques are required to analyze each document. and extract the necessary data in such a way that the obstacle of the structure can be circumvented.
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References
Garcia, E. (2020, May 1). Text Clustering. Este es uno de los temas más… | by Erick Garcia Ortiz. Medium. Recuperado 27 de agosto de 2023, desde https://medium.com/@egocv/text-clustering-cdb6515bdc52
Introducción al topic modeling con Gensim (I): fundamentos y preprocesamiento de textos. (2021, March 18). Divulgando Machine Learning - El mundo de los datos. Recuperado 27 de agosto de 2023, desde https://elmundodelosdatos.com/topic-modeling-gensim-fundamentos-preprocesamiento-textos/
Introducción al topic modeling con Gensim (II): asignación de tópicos. (2021, March 31). Divulgando Machine Learning - El mundo de los datos. Recuperado 27 de agosto de 2023, desde https://elmundodelosdatos.com/topic-modeling-gensim-asignacion-topicos/
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