Abstract: A method and system for training an artificial neural network (“ANN”) are disclosed. One embodiment of the method of the present invention initializes an artificial neural network by assigning values to one or more weights. An adaptive learning rate is set to an initial starting value and training patterns for an input layer and an output layer are stored. The input layer training pattern is processed in the ANN to obtain an output pattern. An error is calculated between the output layer training pattern and the output pattern and used to calculate an error ratio, which is used to adjust the value of the adaptive learning rate. If the error ratio is less than a threshold value, the adaptive learning rate can be multiplied by a step-up factor to increase the learning rate. If the error ratio is greater than the threshold value, the adaptive learning rate can be multiplied by a step-down factor to reduce the learning rate.

Abstract: A method and system for dynamically searching databases in response to a query is provided by the present invention. More specifically, a system and method for dynamic data-mining and on-line communication of customized information. This method includes the steps of first creating a search-specific profile. This search-specific profile is then input into a data-mining search engine. The data-mining search engine will mine the search-specific profile to determine topic of interests. These topics of interest are output to at least one search tool. These search tools match the topics of interest to at least one destination data site wherein the destination data sites are evaluated to determine if relevant information is present in the destination data site. Relevant information is filtered and presented to the user making the inquiry.