AI for information technology operation (AIOps): a review of IT incident risk prediction
Ahmed, Salman, Singh, Muskaan, Doherty, Brendan, Ramlan, Effirul, Harkin, Kathryn and Coyle, Damien (2023) AI for information technology operation (AIOps): a review of IT incident risk prediction. In: International Conference on Soft Computing & Machine Intelligence (ISCMI), 26th-27th November 2022, Toronto, Canada.
Full text not available from this repository. (Request a copy)Abstract
The advancement of Artificial Intelligence has led to a surge in its application in Information Technology (IT) Operations, often termed Artificial Intelligence for IT Operations (AIOPS). One of the most challenging problems in AIOPS is IT Service Management (ITSM), which deals with incidents and anomalies of users, often referred to as tickets. These tickets are resolved by the IT firm support system, which plays a significant role in the company's user experiences, productivity, and profit. Recent advances have been made to automate the prediction of IT incidents and resolve them in a minimal time, utilizing AI models. In this paper, we take stock of the work in this domain and review the challenges. We also highlight the open topics that require further investigation for the advancement of the field.
Item Type: | Conference or Workshop Item (Paper) |
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Uncontrolled Keywords: | computing, AI, Artificial Intelligence |
Subjects: | Q Science > QA Mathematics > QA76 Computer software |
Divisions: | Other Departments (Central units) > Research & Enterprise |
Depositing User: | Salman Ahmed |
Date Deposited: | 25 Sep 2023 07:46 |
Last Modified: | 25 Sep 2023 07:46 |
URI: | https://oars.uos.ac.uk/id/eprint/3345 |