Method of natural language processing and data mining techniques applied to the classification of computer incidents

Authors

  • Diana Maribel Garcés-Eslava Universidad de Lima (Perú)

DOI:

https://doi.org/10.26439/interfases2019.n012.4635

Keywords:

risk analysis, computer incidents, service desk, data mining, emergency level

Abstract

This article presents a methodology that applies natural language processing and classification algorithms by us­ing data mining techniques, and incorporating procedures for validation and verification of significance. This is conducted according to the analysis and selection of data and results based on quality statistical analysis, which guarantees the effectiveness percentage in knowledge construction. The analysis of computer incidents within an educational institution and a standardized database of historical computer incidents collected by the Service Desk area is used as case study. Such area is linked to all information technology processes and focuses on the support requirements for the performance of employee activities. As long as users’ requirements are not fulfilled in a timely manner, the impact of incidents may give rise to work problems at different levels, making it difficult to plan or prevent incidents resolution due to their unforeseen nature.

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Author Biography

  • Diana Maribel Garcés-Eslava, Universidad de Lima (Perú)

    Egresada de la Carrera de Ingeniería de Sistemas de la Universidad de Lima. Labora en el área de Sistemas-Producción como analista de producción junior en la Asociación Cultural Peruano Británica. Sus áreas de interés son técnicas de minería de datos, métodos de procesamiento de lenguaje natural y aprendizaje automático.

References

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Published

2019-12-09

Issue

No. 012 (2019)

Section

Research papers

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Last updated 03/05/21

How to Cite

Garcés-Eslava, D. M. (2019). Method of natural language processing and data mining techniques applied to the classification of computer incidents. Interfases, 12(012), 11-29. https://doi.org/10.26439/interfases2019.n012.4635