Xiruxe: An intelligent fault tracking tool

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

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

6 Atıf (Scopus)

Özet

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%.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıInternational Conference on Artificial Intelligence and Pattern Recognition 2009, AIPR 2009
Sayfalar293-300
Sayfa sayısı8
Yayın durumuYayınlandı - 2009
Harici olarak yayınlandıEvet
Etkinlik2009 International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2009 - Orlando, FL, United States
Süre: 13 Tem 200916 Tem 2009

Yayın serisi

AdıInternational Conference on Artificial Intelligence and Pattern Recognition 2009, AIPR 2009

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???event.eventtypes.event.conference???2009 International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2009
Ülke/BölgeUnited States
ŞehirOrlando, FL
Periyot13/07/0916/07/09

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