Data mining: concepts and techniques
Data mining: concepts and techniques
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
Time Series Prediction and Neural Networks
Journal of Intelligent and Robotic Systems
Knowledge Discovery from Telecommunication Network Alarm Databases
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Recent Advances and Research Problems in Data Warehousing
ER '98 Proceedings of the Workshops on Data Warehousing and Data Mining: Advances in Database Technologies
Industry: predicting telecommunication equipment failures from sequences of network alarms
Handbook of data mining and knowledge discovery
A symbolic representation of time series, with implications for streaming algorithms
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequence
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Perception based time series data mining with MAP transform
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Knowledge discovery in time series databases
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Online hybrid traffic classifier for Peer-to-Peer systems based on network processors
Applied Soft Computing
Real anomaly detection in telecommunication multidimensional data using data mining techniques
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume PartI
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Over the last years, the data generated in Telecommunications Networks has reached unmanageable limits of information. Data Mining (DM) techniques have showed their advantages on helping to manage this information and transforming it in useful knowledge. However, due to the dynamics of the environment of Telecommunications Networks, the simple application or adaptation of DM techniques is not enough to obtain timely a deeper knowledge. In this paper, this problem is addressed by applying DM techniques in real time. First, we propose a methodology taking into account all the processes involved in transforming telecommunications data into information, and finally to knowledge. Second, we propose a framework for the utilization of Intelligent Agents to help the process of DM in real time. To illustrate our approach, we describe a real-life case study based on the integration of Intelligent Agents and DM technologies for obtaining in real time knowledge that is critical for managing telecommunication networks.