| _version_ | 1866901564608741376 |
|---|---|
| author | Rakesh Rohan Budige |
| author_facet | Rakesh Rohan Budige |
| contents | <h2>Abstract</h2> <p>Unstructured data that makes up almost 80–90% of the world’s digitized information poses great challenges in extraction, interpretation, and decision-making because of the lack of a pre-defined format and the complexity of semantics. Natural Language Processing (NLP) has been a pivotal discipline to overcome the challenges and has itself maturated from rule-driven systems to transformer centered architectures that can comprehend the context of the language. Of these developments, ChatGPT is a formidable generative model that integrates deep learning with linguistic reasoning in order to comprehend and synthesize unstructured data at a very large scale. The present paper theorizes the role of ChatGPT and NLP in the analysis of unstructured data and outlines the main applications in business intelligence, healthcare, engineering, and cyber-security spaces. Advantages are in terms of scalability, contextual precision, and flexibility with the shortcomings ranging from hallucination to bias and domain adaptation challenges. The paper concludes the discussion by charting the future of infusing ChatGPT with explainable AI, knowledge graphs, and multimodal systems. All in all, the present paper theorizes the role of NLP and ChatGPT in terms of deriving actionable knowledge from unstructured data.</p> <p><strong>Keywords-</strong> <strong>ChatGPT, Natural Language Processing (NLP), Unstructured Data Analysis, Transformer Models, Artificial Intelligence Applications</strong></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17068541 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | ChatGPT and NLP as Tools for Unstructured Data Analysis Rakesh Rohan Budige <h2>Abstract</h2> <p>Unstructured data that makes up almost 80–90% of the world’s digitized information poses great challenges in extraction, interpretation, and decision-making because of the lack of a pre-defined format and the complexity of semantics. Natural Language Processing (NLP) has been a pivotal discipline to overcome the challenges and has itself maturated from rule-driven systems to transformer centered architectures that can comprehend the context of the language. Of these developments, ChatGPT is a formidable generative model that integrates deep learning with linguistic reasoning in order to comprehend and synthesize unstructured data at a very large scale. The present paper theorizes the role of ChatGPT and NLP in the analysis of unstructured data and outlines the main applications in business intelligence, healthcare, engineering, and cyber-security spaces. Advantages are in terms of scalability, contextual precision, and flexibility with the shortcomings ranging from hallucination to bias and domain adaptation challenges. The paper concludes the discussion by charting the future of infusing ChatGPT with explainable AI, knowledge graphs, and multimodal systems. All in all, the present paper theorizes the role of NLP and ChatGPT in terms of deriving actionable knowledge from unstructured data.</p> <p><strong>Keywords-</strong> <strong>ChatGPT, Natural Language Processing (NLP), Unstructured Data Analysis, Transformer Models, Artificial Intelligence Applications</strong></p> |
| title | ChatGPT and NLP as Tools for Unstructured Data Analysis |
| url | https://doi.org/10.5281/zenodo.17068541 |