Recommendation for Decision Support on Cloud Data Center based on Operation and Maintenance Knowledge Graph

DOI

10.2991/978-94-6463-042-8_185How to use a DOI?

Keywords

Recommendation; operation and maintenance Knowledge Graph; decision support; Cloud Data Center

Abstract

With the rapid development of Cloud Data Center, the recommendation systems that provide valuable suggestions for the users to address the problem of information over-loaded have provoked a vast amount of attention and research from multiple disciplines. In recent decades, both the matrix factorization (MF) and deep learning methods have achieved fairly good performance for the recommendation. However, in the field of Operation And Maintenance (OAM) cloud data center, due to the intricate nature of the faults data in multi-level and diversified OAM scenarios, the sparsity of data may lead to significant degradation of recommendation performance, which pose huge challenges to the existing recommendation methods. To address these problems, in this paper, we propose a recommendation method for Decision Support on Cloud Data Center based on the operation and maintenance Knowledge Graph. Specifically, fault-based and solution-based representations are learned for Collaborative Filtering (CF), which has been proven to be one of the most commonly applied and successful recommendation approaches. Meanwhile, faults’ attributions are combined into the representations by OAM Knowledge Graph for alleviating the sparsity problem. Experimental results demonstrated the effectiveness of our proposed method in the OAM cloud data center for decision support.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Hongbo Lu
AU  - Yiyou Yuan
AU  - Dequan Gao
AU  - Ziyan Zhao
AU  - Fenggang Lai
AU  - Chao Ma
AU  - Hao Xu
AU  - Yin Liu
PY  - 2022
DA  - 2022/12/29
TI  - Recommendation for Decision Support on Cloud Data Center based on Operation and Maintenance Knowledge Graph
BT  - Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022)
PB  - Atlantis Press
SP  - 1289
EP  - 1293
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-042-8_185
DO  - 10.2991/978-94-6463-042-8_185
ID  - Lu2022
ER  -