Experimental results on a constraint based sequential pattern mining for telecommunication alarm data
Journal
2nd International Conference on Web Information Systems Engineering, WISE 2001
Journal Volume
2
Pages
186-193
Date Issued
2001
Author(s)
Abstract
A telecommunication system produces daily a large amount of alarm data which contains hidden valuable information about the system behavior The knowledge discovered from alarm data can be used in finding problems in networks and possibly in predicting severe faults. In this paper we devise a solution procedure for mining sequential alarm patterns from the alarm data of a GSM system. First, by observing the features of the alarm data, we develop operations for data cleaning without compromising the quality of sequential alarm patterns obtained. After the data cleaning procedure, we transform the alarm data into a set of alarm sequences. Note that the consecutive alarm events exist in the alarm sequences, and it is complicated to count the occurrence counts of events and extract patterns. Hence, we devise a new counting method to determine the occurrence count of the sequential alarm patterns in accordance with the nature of alarms. More importantly, by utilizing time constraints to restrict the time difference between two alarm events, we devise a mining algorithm to discover useful sequential alarm patterns. The proposed mining algorithm is implemented and applied to test against a set of real alarm data provided by a cellular phone company. © 2001 IEEE.
Subjects
Cellular phones; Cleaning; Data mining; Databases; Electronic mail; GSM; Information systems; Testing; Time factors; Wireless communication
Other Subjects
Alarm systems; Algorithms; Cellular telephone systems; Cellular telephones; Cleaning; Database systems; Electronic mail; Global system for mobile communications; Information systems; Mobile phones; Systems engineering; Telephone sets; Testing; Wireless telecommunication systems; World Wide Web; Cellular Phone; Constraint-based sequential pattern minings; Mining algorithms; Solution procedure; Telecommunication alarm; Time factors; Time-differences; Wireless communications; Data mining
Type
conference paper
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