A Comparative Analysis of Machine Learning Algorithms for Text Analysis [Articol]
| dc.contributor.author | Parahonco, Alexandr | en |
| dc.contributor.author | Petic, Mircea | en |
| dc.date.accessioned | 2025-07-07T11:57:03Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | This article proposes a system of metrics for estimating text fetched from the Internet and selecting the one that should be further summarized. The research examines algorithms and software for determining user preferences, employing natural language processing (NLP) and supervised learning classification methods. An empirical assessment is conducted across academic, security, and non-security domains. The paper concludes with insights on the experimental results and the potential future of the implemented metric system. | en |
| dc.description.sponsorship | This article was written within the framework of the research project 011301 “Information systems based on Artificial Intelligence”. | en |
| dc.identifier.citation | PARAHONCO, Alexandr and Mircea PETIC. A Comparative Analysis of Machine Learning Algorithms for Text Analysis. In: International Conference dedicated to the 60th anniversary of the foundation of Vladimir Andrunachievici Institute of Mathematics and Computer Science, MSU, October 10-13 2024. Chisinau: [S. n.], 2024, pp. 350-360. ISBN 978-9975-68-515-3. | en |
| dc.identifier.isbn | 978-9975-68-515-3 | |
| dc.identifier.uri | https://msuir.usm.md/handle/123456789/18272 | |
| dc.language.iso | en | |
| dc.subject | texts metrics | en |
| dc.subject | NLP | en |
| dc.subject | classification | en |
| dc.subject | supervised learning | en |
| dc.title | A Comparative Analysis of Machine Learning Algorithms for Text Analysis [Articol] | en |
| dc.type | Article |