Xiruxe: An intelligent fault tracking tool

Ayse Bakir, Ekrem Kocaguneli, Ayse Tosun, Ayse Bener, Burak Turhan

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

6 Citations (Scopus)

Abstract

Fault localization in telecommunication sector is a major challenge. Most companies manually try to trace faults back to their origin. Such a process is expensive, time consuming and ineffective. Therefore in this study we automated manual fault localization process by designing and implementing an intelligent software tool (Xiruxe) for a local telecommunications company. Xiruxe has a learning-based engine which uses powerful AI algorithms, such as Naïve Bayes, Decision Tree and Multi Layer Perceptrons, to match keywords and patterns in the fault messages. The initial deployment results show that this intelligent engine can achieve a misclassification rate as low as 1.28%.

Original languageEnglish
Title of host publicationInternational Conference on Artificial Intelligence and Pattern Recognition 2009, AIPR 2009
Pages293-300
Number of pages8
Publication statusPublished - 1 Dec 2009
Externally publishedYes
Event2009 International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2009 - Orlando, United States of America
Duration: 13 Jul 200916 Jul 2009

Conference

Conference2009 International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2009
CountryUnited States of America
CityOrlando
Period13/07/0916/07/09

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