Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Escrow techniques for mobile sales and inventory applications
Wireless Networks
Data mining: concepts and techniques
Data mining: concepts and techniques
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Knowledge Discovery from Telecommunication Network Alarm Databases
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
SPIRIT: Sequential Pattern Mining with Regular Expression Constraints
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Interactive Constraint-Based Sequential Pattern Mining
ADBIS '01 Proceedings of the 5th East European Conference on Advances in Databases and Information Systems
Efficient Mining of Partial Periodic Patterns in Time Series Database
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Supporting collaborative applications in a heterogeneous mobile environment
Computer Communications
A sampling-based framework for parallel data mining
Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming
SO_MAD: SensOr Mining for Anomaly Detection in Railway Data
ICDM '09 Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects
ICDM'10 Proceedings of the 10th industrial conference on Advances in data mining: applications and theoretical aspects
Anomaly detection in monitoring sensor data for preventive maintenance
Expert Systems with Applications: An International Journal
Generating touring path suggestions using time-interval sequential pattern mining
Expert Systems with Applications: An International Journal
Predictive combinations of monitor alarms preceding in-hospital code blue events
Journal of Biomedical Informatics
Sequential pattern mining -- approaches and algorithms
ACM Computing Surveys (CSUR)
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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 tile alarm data, we develop operations for data cleaning. Then, 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 procedure to determine the occurrence count of the sequential alarm patterns in accordance with the nature of alarms. By utilizing time constraints to restrict tile 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. The quality of knowledge discovered is evaluated. The experimental results show that the proposed operations of data cleaning are able to improve tile execution of our mining algorithm significantly and tile knowledge obtained from the alarm data is very useful from tile perspective of network operators for alarm prediction and alarm control.