SaaS software performance issue diagnosis using independent component analysis and restricted Boltzmann machine
SaaS software performance issue diagnosis using independent component analysis and restricted Boltzmann machine
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使用独立组件分析和受限玻尔兹曼机进行 SaaS 软件性能问题诊断
DOI：
10.1002/cpe.5729
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发表时间：
2020-05
影响因子：
2
通讯作者：
Ying Shi
中科院分区：
文献类型：
--
作者：
Wang Rui;Ying Shi
SaaS软件性能问题诊断旨在对性能记录的类型进行分类。深层分类方法已获得了很多关注，以此来构建少数标记数据的层次表示。但是，有
SaaS software performance issue diagnosis aims to classify the type of the performance records. Deep classification method has gained much attention as a way to construct hierarchical representations from a small amount of labeled data. However, there are few researches on how to solve the classification problem of performance issues by using the deep classification method. In addition, shallow classification methods exist some problems, such as the training sample is large and the ability to fit complex functions is weak. In this article, we proposed a deep performance issue classification method based on Independent Component Analysis (ICA) and Restricted Boltzmann Machine (RBM). ICA is used to extract the features, after this process, the classification feature is obtained as RBM input, and the extracted information about performance issue is transformed into identifiable information for the classifier via visible structure of input; Hidden layer for RBM is built to realize the data transmission between hidden structure, keeping the key information; And the classification algorithm is implemented to solve our performance issue diagnosis problem of SaaS software. Experiments show that the performance of our approach is superior to the classical shallow classification algorithm, and it also meet the efficiency requirement.
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DOI：
10.1007/978-1-4899-7687-1_810
发表时间：
2017
期刊：
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影响因子：
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作者：
Xinhua Zhang
通讯作者：
Xinhua Zhang
DOI：
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发表时间：
2005
期刊：
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影响因子：
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作者：
M. A. Carreira-Perpiñán;Geoffrey E. Hinton
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M. A. Carreira-Perpiñán;Geoffrey E. Hinton
DOI：
10.1016/j.jss.2013.09.013
发表时间：
2014
期刊：
J. Syst. Softw.
影响因子：
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作者：
C. Bezemer;A. Zaidman
通讯作者：
C. Bezemer;A. Zaidman
DOI：
10.1201/9781003139041-11
发表时间：
2021-03
期刊：
An Introduction to IoT Analytics
影响因子：
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作者：
Harry G. Perros
通讯作者：
Harry G. Perros
使用 HMRF-MAP 框架识别 SaaS 软件性能问题
DOI：
10.1002/spe.2607
发表时间：
2018
期刊：
Software: Practice and Experience
影响因子：
--
作者：
Rui Wang;Shi Ying
通讯作者：
Shi Ying