Incident Management Optimization through the Reuse of Experiences and Natural Language Processing

Bezerra, Glauber de Tarso Vieira; Pinheiro, Vládia; Albuquerque, Adriano Bessa

doi:10.1109/quatic.2014.63

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2018

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“…Initially, it is necessary that incidents be recorded or reported to a service center, generating software maintenance experiences databases. Several researches have proposed the reuse of experiences in Incident Management [1] and models such as the Information Technology Infrastructure Library (ITIL), contributing, for example, to the compliance with the rules of priority and time of attendance of the registered incidents, defined in Service Level Agreements (SLA).…”

Section: Introductionmentioning

confidence: 99%

XMILE - An Expert System for Maintenance Learning from Textual Reports (S)

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Pinheiro

2018

International Conferences on Software Engineering and Knowledge Engineering

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Software incidents are normally described in natural language (like English or Portuguese languages), because the users become free to express themselves about the incident. In this paper, we propose XMILE-an eXpert MaIntenance LEarning system based on NLP (Natural Language Processing) and machine learning techniques, that is capable of inferring the main attributes (type of intervention, maintenance action, cause and faulty zone) from textual reports of incidents. The XMILE was used on a real set of reports of maintenance incidents performed on IT systems of a Brazilian automobile enterprise, with excellent results in terms of precision and recall metrics.

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Section: Introductionmentioning

confidence: 99%