Developing Robust Entity Recognition Models Using Natural Language Processing and Artificial Intelligence for Enterprise Document Classification and Content Management Automation
Keywords:
Natural Language Processing, Named Entity Recognition, Document Classification, Content Management, Enterprise Automation, Artificial IntelligenceAbstract
The exponential growth of unstructured data in enterprise environments necessitates advanced automation techniques to support document classification and content management. Natural Language Processing (NLP) and Artificial Intelligence (AI), particularly Named Entity Recognition (NER), have emerged as pivotal tools in parsing and understanding large document corpora. This paper presents a comprehensive framework for building robust NER models tailored for enterprise contexts, incorporating both rule-based and machine learning approaches. It explores recent methodologies in NLP and their integration with AI to automate document workflows, enhance information retrieval, and ensure compliance in enterprise knowledge systems.
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Copyright (c) 2024 García Lorca Vallejo (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
