Kazuo J. Ezawa and Steven W. Norton. Constructing bayesian networks to predict uncollectible telecommunications accounts. IEEE Expert, 11(5):45--51, October 1996. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Intelligent Telecommunication Technologies - Weiss, Eddy, Weiss (1998) (Correct)
....industry incurs billions of dollars of uncollectible debt each year. The Advanced Pattern Recognition and Identification (APRI) system was developed by AT T s Consumer Laboratory to predict the probability of uncollectible debt based on historical data, including data of past uncollectibles [16]. The output of APRI is fed into a decision support system which can take a variety of actions, including blocking a call from being completed. APRI automatically constructs Bayesian network models for classification problems using extremely large databases. Bayesian networks were chosen for this ....
Ezawa, K., Norton, S. (1996), Constructing Bayesian Networks to Predict Uncollectible Telecommunication Accounts, IEEE Expert, Vol. 11, No. 5, Oct., pp. 45-50.
Probability Bounds for Goal Directed Queries in Bayesian.. - Mannino, Mookerjee (Correct)
....particular state. For example, a manager may pose the query: Is P(Customer is Non Paying evidence) 0.80 This question contains the Goal of Non Paying with probability intervals [0, 0.80] and (0. 80, 1] This kind of question is frequently posed in service industries such as telecommunications [Ezawa and Norton, 1996]. Depending on the range of available actions, managers may use queries with more than two probability Page 2 intervals. To answer such queries, a large set of potential, costly inputs may be available. Therefore, the costs of acquiring the information necessary to answer such questions can be ....
Ezawa, K. and Norton, S. "Constructing Bayesian Networks to Predict Uncollectible Telecommunications Accounts," IEEE Expert 11, 5 (October 1996), 45-51.
Adaptive Fraud Detection - Fawcett, Foster (1997) (40 citations) (Correct)
....transactions are fraudulent. In our domain, we found that DC 1 significantly improves detection performance over systems that use transaction classification alone. It would be interesting to determine whether a system like DC 1 could improve performance on these other superimposition fraud tasks. Ezawa and Norton (1995, 1996) have addressed the problem of uncollectible debt in telecommunications services. They use a goal directed Bayesian network for classification, which distinguishes customers who are likely to default from those who are not. As with our work, Ezawa and Norton s work faces problems with unequal ....
Ezawa, K. and S. Norton (1996, October). Constructing bayesian networks to predict uncollectible telecommunications accounts. IEEE Expert, 45--51.
Privacy Preserving k means clustering over Vertically Partitioned .. - Vaidya (2003) (2 citations) (Correct)
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Kazuo J. Ezawa and Steven W. Norton. Constructing bayesian networks to predict uncollectible telecommunications accounts. IEEE Expert, 11(5):45--51, October 1996.
Input Dependent Misclassification Costs for.. - Hollmen, Skubacz.. (2000) (1 citation) (Correct)
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Kazuo J. Ezawa and Steven W. Norton. Constructing bayesian networks to predict uncollectible telecommunications accounts. IEEE Expert, 11(5):45-- 51, October 1996.
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