A survey of aiops methods for failure management

P Notaro, J Cardoso, M Gerndt - ACM Transactions on Intelligent …, 2021 - dl.acm.org
Modern society is increasingly moving toward complex and distributed computing systems.
The increase in scale and complexity of these systems challenges O&M teams that perform …

An overview of data-driven techniques for IT-service-management

P Kubiak, S Rass - IEEE Access, 2018 - ieeexplore.ieee.org
High availability of information technology (IT)-applications and-infrastructure components is
a significant factor for the success of organizations because more and more business …

Machine learning for discovering missing or wrong protein function annotations: a comparison using updated benchmark datasets

FK Nakano, M Lietaert, C Vens - BMC bioinformatics, 2019 - Springer
Background A massive amount of proteomic data is generated on a daily basis, nonetheless
annotating all sequences is costly and often unfeasible. As a countermeasure, machine …

A survey of aiops for failure management in the era of large language models

L Zhang, T Jia, M Jia, Y Wu, A Liu, Y Yang, Z Wu… - arxiv preprint arxiv …, 2024 - arxiv.org
As software systems grow increasingly intricate, Artificial Intelligence for IT Operations
(AIOps) methods have been widely used in software system failure management to ensure …

Online interactive collaborative filtering using multi-armed bandit with dependent arms

Q Wang, C Zeng, W Zhou, T Li… - … on Knowledge and …, 2018 - ieeexplore.ieee.org
Online interactive recommender systems strive to promptly suggest users appropriate items
(eg, movies and news articles) according to the current context including both user and item …

Active learning for hierarchical multi-label classification

FK Nakano, R Cerri, C Vens - Data Mining and Knowledge Discovery, 2020 - Springer
Due to technological advances, a massive amount of data is produced daily, presenting
challenges for application areas where data needs to be labelled by a domain specialist or …

Multi-label classification based on associations

R Alazaidah, G Samara, S Almatarneh, M Hassan… - Applied Sciences, 2023 - mdpi.com
Associative classification (AC) has been shown to outperform other methods of single-label
classification for over 20 years. In order to create rules that are both more precise and …

Automated IT service desk systems using machine learning techniques

SP Paramesh, KS Shreedhara - … analytics and learning: proceedings of dal …, 2018 - Springer
Managing problem tickets is a key issue in any IT service industry. The routing of a problem
ticket to the proper maintenance team is very critical step in any service desk (Helpdesk) …

Star: A system for ticket analysis and resolution

W Zhou, W Xue, R Baral, Q Wang, C Zeng, T Li… - Proceedings of the 23rd …, 2017 - dl.acm.org
In large scale and complex IT service environments, a problematic incident is logged as a
ticket and contains the ticket summary (system status and problem description). The system …

SDHC: Joint semantic-data guided hierarchical classification for fine-grained HRRP target recognition

Y Liu, T Long, L Zhang, Y Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
High-resolution range profile (HRRP) is increasingly employed in radar target recognition
under intricate ground scenarios. Such scenarios demand recognizing the specific type of a …