Data Mining in Telecommunications

@inproceedings{Weiss2005DataMI,
  title={Data Mining in Telecommunications},
  author={G. Weiss},
  booktitle={The Data Mining and Knowledge Discovery Handbook},
  year={2005}
}
  • G. Weiss
  • Published in
    The Data Mining and Knowledge…
    2005
  • Computer Science
Telecommunication companies generate a tremendous amount of data. These data include call detail data, which describes the calls that traverse the telecommunication networks, network data, which describes the state of the hardware and software components in the network, and customer data, which decsribes the telecommmunication customers. This chapter describes how Data Mining can be used to uncover useful information buried within these data sets. Several Data Mining applications are described… Expand
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References

SHOWING 1-10 OF 16 REFERENCES
Data Mining and Forecasting in Large-Scale Telecommunication Networks
TLDR
The authors present an approach for warehousing data about faulty networks and for mining it to find trends, and have identified several patterns which AT&T can use to improve network reliability. Expand
Giga-Mining
TLDR
The motivation for massive tracking is discussed and the definition and the computation of one of the more interesting bytes in the profile are described and fully described. Expand
Rule Discovery in Telecommunication Alarm Data
TLDR
A novel partial solution to the task of knowledge acquisition for correlation systems is described and a method and a tool for the discovery of recurrent patterns ofalarms in databases, which can be used in the construction of real-time alarm correlation systems are presented. Expand
Discovery of fraud rules for telecommunications—challenges and solutions
TLDR
This work presents as an example a two-stage system based on adaptation of the C4.5 rule generator, with an additional rule selection mechanism, and experimental results indicate that this route is very promising. Expand
Knowledge Discovery in Telecommunication Services Data Using Bayesian Network Models
TLDR
This paper addresses the discovery of predictive knowledge bearing on fraud and uncollectible debt using a supervised machine learning method that constructs Bayesian network models and is able to predict rare event outcomes and cope with the quirks and copious amounts of input data. Expand
Signature-Based Methods for Data Streams
TLDR
The types of features that signature-based methods contain, nuances of how these are updated through time, the treatment of outliers, and the trade-off between time-driven and event-driven processing are discussed. Expand
Adaptive Fraud Detection
TLDR
This paper uses a rule-learning program to uncover indicators of fraudulent behavior from a large database of customer transactions, which are used to create a set of monitors, which profile legitimate customer behavior and indicate anomalies. Expand
Just the fax—differentiating voice and fax phone lines using call billing data
TLDR
An experiment in distinguishing voice and fax customers in a long distance telephony network based on the customers’ calling patterns is surveyed, revealing a hyperplane-separator heuristic developed for this problem whose performance here is comparable to that of an established learning algorithm. Expand
Statistics and data mining techniques for lifetime value modeling
TLDR
Using the proportional hazards and neural network models in tandem, it is demonstrated how data mining tools can be apt complements of the classical statistical models, and show that their combined usage overcomes many of the shortcomings of each separate tool setresulting in a LTV tenure prediction model that is both accurate and understandable. Expand
ANSWER: Network Monitoring Using Object-Oriented Rules
TLDR
ANSWER has been deployed for more than a year and handles all 140 of AT&T's 4ESS switches and processes over 100,000 4ESS alarms per week, resulting in an expert system that is more clearly organized, easily understood and maintainable than its predecessor. Expand
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