Comparative Analysis of Text Mining Techniques for News Article Summarization

Authors

  • Muhammad Aoun CS & IT Department, Ghazi University, Dera Ghazi Khan, Punjab-Pakistan.

DOI:

https://doi.org/10.5281/zenodo.7893329

Keywords:

Mining, Text Mining, Textual Data, Text Mining Techniques

Abstract

Text mining research paper is a scientific study that focuses on the development and application of text mining techniques for extracting valuable information from unstructured textual data. The paper discusses the challenges of working with unstructured data and the need for advanced text mining techniques to address these challenges. The paper outlines the various steps involved in the text mining process, such as data preprocessing, text representation, and feature selection. It discusses the importance of selecting appropriate algorithms for different types of text mining tasks, including text classification, clustering, sentiment analysis, and topic modeling. The paper also discusses the challenges of evaluating text mining models, including issues related to data quality, model performance, and interpretability. It highlights the importance of using appropriate evaluation metrics and techniques to ensure the reliability and validity of the results. Finally, the paper provides case studies and real-world examples of text mining applications in various domains such as healthcare, social media analysis, and financial analysis. It emphasizes the potential of text mining to provide valuable insights and knowledge that can be used to support decision-making in different industries. Overall, the paper highlights the importance of text mining as a powerful tool for analyzing unstructured textual data and provides a comprehensive overview of the key techniques and challenges in this field.

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Published

2023-04-06

How to Cite

Muhammad Aoun. (2023). Comparative Analysis of Text Mining Techniques for News Article Summarization. LC International Journal of STEM (ISSN: 2708-7123), 4(1), 52-63. https://doi.org/10.5281/zenodo.7893329