Preprocessing expert system for mining association rules in telecommunication networks |
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| Authors: | Tong-Yan Li Xing-Ming Li |
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| Affiliation: | 1. Department of Communication Engineering, Chengdu University of Information Technology, Chengdu 610225, China;2. Key Laboratory of Broadband Optical Fiber Transmission and Communication Networks of Ministry of Education, UESTC, Chengdu 610054, China;1. Digital Contents Research Institute, Sejong University, Seoul, Republic of Korea;2. Division of Data Science, Ton Duc Thang University, Ho Chi Minh City, Vietnam;3. Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam;1. National Institute of Water and Atmospheric Research (NIWA), Hamilton, New Zealand;2. Motu Economic and Public Policy Research (Motu), Wellington, New Zealand;3. DairyNZ, Hamilton, New Zealand;4. CDM Smith, Denver, CO, USA;1. Shandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, Jinan 250022, China;2. School of Computer Science and Technology, Shandong University, Jinan 250101, China |
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| Abstract: | Recently, the application of association rules mining becomes an important research area in alarm correlation analysis. However, the original alarms in the telecommunication networks cannot be used to mine association rules directly. This paper proposes a novel preprocessing expert system model to deal with the original alarms. This model uses two important techniques, of which the time window technique is used for converting original alarms into transactions, and the neural network technique can classify the alarms with different levels according to the characteristics of telecommunication networks in order to mine the weighted association rules. Simulation results and the real-world applications demonstrate the effectiveness and practicality of this preprocessing expert system. |
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