Signature based trouble ticket classification

Xu, Jian; Zhang, Hang; Zhou, Wubai; He, Rouying; Li, Tao

doi:10.1016/j.future.2017.07.054

Cited by 11 publications

(3 citation statements)

References 11 publications

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“…Parmar, Biju [37] x Patidar, Agarwal [38] x Saberi, Theobald [39] x Silva, Pereira [9] x Stein, Flath [7] x Qamili, Shabani [3] x x x Zhou, Zhu [40] x Zuev, Kalistratov [10] x Xu, Zhang [41] x Chagnon [4] x Giurgiu, Wiesmann [42] x…”

Section: Sent Pred Othermentioning

confidence: 99%

Improving Support Ticket Systems Using Machine Learning: A Literature Review

Fuchs¹,

Drieschner²,

Wittges³

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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Processing customer support requests via a support ticket system is a key-element for companies to provide support to their customers in an organized and professional way. However, distributing and processing such tickets is much work, increasing the cost for the support providing company and stretching the resolution time. The advancing potential of Machine Learning has led to the goal of automating those support ticket systems. Against this background, we conducted a Literature Review aiming at determining the present state-of-the-art technology in the field of automated support ticket systems. We provide an overview about present trends and topics discussed in this field. During the Literature Review, we found creating an automated incident management tool being the majority topic in the field followed by request escalation and customer sentiment prediction and identified Random Forrest and Support Vector Machine as best performing algorithms for classification in the field.

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Section: Sent Pred Othermentioning

confidence: 99%

Improving Support Ticket Systems Using Machine Learning: A Literature Review

Fuchs¹,

Drieschner²,

Wittges³

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…IT company workers face various difficulties, including challenges with buildings and infrastructure, software, and HR issues. The IT service desk or Helpdesk, which is often accessible over the Internet, is used by employees of an organization to report an issue [3]. The problem tickets will be assigned to the relevant domain expert group or service desk representative based on the ticket category.…”

Section: Introductionmentioning

confidence: 99%

Utilizing deep learning, feature ranking, and selection strategies to classify diverse information technology ticketing data effectively

Deshai

Rao

Chittineni

et al. 2023

IJ-AI

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In today's internet world, information technology (IT) ticketing services are potentially increasing across many corporations. Therefore, the automatic classification of IT tickets becomes a significant challenge. Feature selection becomes most important, particularly in data sets with several variables and features. However, enhance classification's precision and performance by stopping insignificant variables. Through our earlier research, we have categorized the unsupervised ticket dataset. As a result, we have converted the dataset into a supervised dataset. In this article, the classification of different IT tickets on Machine learning algorithms, Feature ranking, and feature selection techniques are used to improve the efficiency of machine learning algorithms. However, compared to the machine learning (ML) algorithms, the convolutional neural network (CNN) algorithm provides a better classification of the token IDs and provide better accuracy.

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“…Once an incident ticket appears, we need rapid allocation of skilled maintenance experts to bring an abnormal service back to normal, which highly depends on the accurate ticket classification. As an initial step of rapid management, ticket classification is used to identify problem types of tickets based on the problem descriptions recorded in tickets [1], [2]. In a typical ticket system, the ticket classification is done manually by system administrators to assign a problem type.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Output Support Vector Machine Based Incident Ticket Classification

Yang

2021

IEICE Trans. Inf. & Syst.

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Signature based trouble ticket classification

Cited by 11 publications

References 11 publications

Improving Support Ticket Systems Using Machine Learning: A Literature Review

Improving Support Ticket Systems Using Machine Learning: A Literature Review

Utilizing deep learning, feature ranking, and selection strategies to classify diverse information technology ticketing data effectively

Fuzzy Output Support Vector Machine Based Incident Ticket Classification

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