ice provider is prohibited from using the information to try to get the customer back (e.g., by only targeting profitable customers). Furthermore, companies are prohibited from using data from one type of service (e.g., wireless) in order to sell another service (e.g.. landline services). Thus, the use of data mining is restricted in that there are many instances in which useful knowledge extracted by the data mining process cannot be legally exploited. Much of the rationale for these prohibitions relates to competition. For example, if a large company can leverage the data associated with one service to sell another service, then companies that provide fewer services would be at a competitive disadvantage. The telecommunications industry has been one of the earliest adopters of data mining technology, largely because of the amount and quality of the data that it collects. This has resulted in many successful data mining applications. Given the fierce competition in the telecommunications industry, one can only expect the use of data mining to accelerate, as companies strive to operate more efficiently and gain a competitive advantage. REFERENCES Cortes, C., Pregibon, D. Signature-based methods for data streams. Data Mining and Knowledge Discovery 2001; 5(3):167-182. Cortes, C., Pregibon, D. Giga-mining. Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining; 174-178, 1998 August 27-31; New York, NY: AAAI Press, 1998. Ezawa, K., Norton, S. Knowledge discovery in telecommunication services data using Bayesian network models. Proceedings of the First International Conference on Knowledge Discovery and Data Mining; 1995 August 20-21. Montreal Canada. AAAI Press: Menlo Park, CA, 1995. Fawcett, T., Provost, F. Adaptive fraud detection. Data Mining and Knowledge Discovery 1997; 1(3):291-316. Fawcett, T, Provost, F. Activity monitoring: Noticing interesting changes in behavior. Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; 53-62. S