Abstract: A system and method for searching documents in a data source and more particularly, to a system and method for analyzing and clustering of documents for a search engine. The system and method includes analyzing and processing documents to secure the infrastructure and standards for optimal document processing. By incorporating Computational Intelligence (CI) and statistical methods, the document information is analyzed and clustered using novel techniques for knowledge extraction. A comprehensive dictionary is built based on the keywords identified by the these techniques from the entire text of the document. The text is parsed for keywords or the number of its occurrences and the context in which the word appears in the documents. The whole document is identified by the knowledge that is represented in its contents. Based on such knowledge extracted from all the documents, the documents are clustered into meaningful groups in a catalog tree.

Abstract: A method and system for searching a document source. The method includes analyzing a query and then creating a query pattern. A document is search in a document source which match the query pattern. The retrieved documents are divided into subsets of similar documents, where each subset of the subsets of similar documents is described in terms of a subset pattern. An ordered list of clusters based on the subset pattern of each subset of similar documents is then retrieved. The ordered list of clusters includes separate clusters which contain similar documents retrieved in response to the query. A machine readable medium containing code for searching a document source is also provided.

Abstract: A test case generator which converts a real-world problem into an artificial landscape that preserves the main characteristics of the problem. A plurality of input parameters is used to define initial components of a feasibility space within a search space. The components are randomly enlarged and complexity is added. The results of a series of runs within the feasibility space are compared to arrive at a recommended optimization method. A computer program that runs on a workstation or personal computer implements the method of the invention. The test case generator can be applied to numerous types of problems.

Abstract: A method and system for returning an optimum (or near-optimum) solution to a nonlinear programming problem. By specifying a precision coefficient, the user can influence the flexibility of the returned solution. A population of possible solutions is initialized based on input parameters defining the problem. The input parameters may include a minimum progress and a maximum number of iterations having less the minimum progress. The solutions are mapped into a search space that converts a constrained problem into an unconstrained problem. Through multiple iterations, a subset of solutions is selected from the population of solutions, and variation operators are applied to the subset of solutions so that a new population of solutions is initialized and then mapped. If a predetermined number of iterations has been reached, that is if the precision coefficient has been satisfied, the substantially optimum solution is selected from the new population of solutions.