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All Journal Indonesian Journal of Electrical Engineering and Computer Science
Jose Luis Herrera Salazar
Universidad Autónoma de Ica

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Search and classify topics in a corpus of text using the latent dirichlet allocation model Orlando Iparraguirre-Villanueva; Fernando Sierra-Liñan; Jose Luis Herrera Salazar; Saul Beltozar-Clemente; Félix Pucuhuayla-Revatta; Joselyn Zapata-Paulini; Michael Cabanillas-Carbonell
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp246-256

Abstract

This work aims at discovering topics in a text corpus and classifying the most relevant terms for each of the discovered topics. The process was performed in four steps: first, document extraction and data processing; second, labeling and training of the data; third, labeling of the unseen data; and fourth, evaluation of the model performance. For processing, a total of 10,322 "curriculum" documents related to data science were collected from the web during 2018-2022. The latent dirichlet allocation (LDA) model was used for the analysis and structure of the subjects. After processing, 12 themes were generated, which allowed ranking the most relevant terms to identify the skills of each of the candidates. This work concludes that candidates interested in data science must have skills in the following topics: first, they must be technical, they must have mastery of structured query language, mastery of programming languages such as R, Python, java, and data management, among other tools associated with the technology.
Cybersecurity in health sector: a systematic review of the literature Catherine Vanessa Peve Herrera; Jonathan Steve Mendoza Valcarcel; Mónica Díaz; Jose Luis Herrera Salazar; Laberiano Andrade-Arenas
Indonesian Journal of Electrical Engineering and Computer Science Vol 31, No 2: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v31.i2.pp1099-1108

Abstract

Currently, health centers are being affected by various cyberattacks putting at risk the confidential information of their patients and the organization because they do not have a plan or tools to help them mitigate these cyberattacks, which is important to know what measures to take to protect the privacy of personal data. The present work was carried out under a systematic literature review, which aims to show the importance of cybersecurity in the health sector knowing which tools are the most used and efficient to prevent a cyberattack. A systematic review of 301 articles was carried out, 79 of which are aligned with the objective set, fulfilling the inclusion and exclusion criteria. The search for information was carried out in the Scopus and Dimensions databases. The analysis carried out has resulted in good information that was compiled for the development of this topic, being favorable thanks to the different research of different authors.
Co-Authors Catherine Vanessa Peve Herrera Félix Pucuhuayla-Revatta Fernando Sierra-Liñan Jonathan Steve Mendoza Valcarcel Joselyn Zapata-Paulini Laberiano Andrade-Arenas Michael Cabanillas-Carbonell Mónica Díaz Orlando Iparraguirre-Villanueva Saul Beltozar-Clemente