Organizing a network of databases using probabilistic reasoning

Due to the complexity of real-world applications, the number of databases and the volumes of data in databases have increased tremendously. With the explosive growth in the amount and complexity of data, how to effectively organize the databases and utilize the huge amount of data becomes important. For this purpose, a probabilistic network that organizes a network of databases and manages the data in the databases is proposed. Each database is represented as a node in the probabilistic network and the affinity relations of the databases are embedded in the proposed Markov model mediator (MMM) mechanism. Probabilistic reasoning is used to formulate and derive the probability distributions for an MMM. Once the probability distributions of each MMM are generated, a stochastic process is conducted to calculate the similarity measures for pairs of databases. The similarity measures are transformed into the branch probabilities of the probabilistic network. Then, the data in the database can be managed and utilized to allow user queries for database searching and information retrieval. An example is included to illustrate how to model each database into an MMM and how to organize the network of databases into a probabilistic network