Approximate representation of probabilistic data in expert systems

Article Abstract:

The use of tree-structures and third-order approximations for characterizing probabilistic distributions in expert systems was compared. The comparison, which was carried out on a reliability problem over a wide range of probability distributions using the I-Divergence criteria, showed that third-order representations lead to reduced losses and maximum entropy solutions. Consequently, a decomposition method for obtaining exact solutions to large-sized problems was developed.

Information Theory, Information technology, Tree structures (Computers), Tree structures (Data structures), Approximation theory, Approximation

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Exact algorithms for the stochastic shortest path problem with a decreasing deadline utility function

Article Abstract:

Exact algorithms that use two types of pruning schemes employed in labeling procedures are developed to solve even large size problems rapidly. One type of pruning adopts the concept of local preference relations while the other applies relaxations. Two algorithms are developed which both contain equal preference relation but two varied relaxations. Both algorithms solve even large problems by citing a very small percentage of all paths.

Management-Problem Solving, Analysis, Usage, Human resource management, Algorithms, Problem solving, Stochastic approximation

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AMOS - a probability-driven, customer-oriented decision support system for target marketing of solo mailings

Article Abstract:

A decision support system for the direct marketing activities of Franklin Mint of Philadelphia, PA, has been developed. Dubbed AMOS, the system supports the company's aim of reducing solo mailings and maximizing profits by targeting the right customers for each promotion campaign. To do this, it derives a customer's purchase probability using expert system, optimization and statistical methods.

Information management, Mail-order industry, Mail order business, Franklin Mint Corp.

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