H1.9.1 Telecommunications Network Diagnosis
|
Abstract:
The Scrubber 3 system monitors problems in the local loop of the telephone network, making automated decisions on tens of millions of cases a year, many of which lead to automated actions. Scrubber saves Bell Atlantic millions of dollars annually, by reducing the number of inappropriate technician dispatches. Scrubber's core knowledge base, the Trouble Isolation Module (TIM), is a probability estimation tree constructed via several data mining processes. TIM currently is deployed in the Delphi system, which serves knowledge to multiple applications. As compared to previous approaches, TIM is more general, more robust, and easier to update when the network or user requirements change. Under certain circumstances it also provides better classications. In fact, TIM's knowledge is general enough that it now serves a second deployed application. One of the most interesting aspects of the construction of TIM is that data mining was used not only in the traditional sense, namely, building a model from a warehouse of actual historical cases. Data mining also was used
Citations
| 3215 | C4.5: Programs for Machine Learning – Quinlan - 1993 |
| 140 | Concept learning and the problem of small disjuncts – Holte, Acker, et al. - 1989 |
| 75 | Fast eective rule induction – Cohen - 1995 |
| 52 | Small disjuncts in action: Learning to diagnose errors in the local loop of the telephone network – Danyluk, Provost - 1993 |
| 1 | Problem de data cleaning and evaluation: a classi learning case study." Informatica – Provost, Danyluk - 1999 |
