Global optimization strategies for indexing, ranking and clustering multimedia documents

摘要

A method for a system that indexes, ranks, and clusters multimedia documents using assessment means, scoring means, stochastic means, and organizing means that optimizes parameter sets comprising of object parameters. The method creates a plurality of individual parameter sets, the parameter sets comprising information sharing system object parameters for describing a model, structures, shape, design, process, search query sets, and dynamic search spaces to be optimized using selective variations, constructive variations, clustering variations, and stochastic variations. The optimizations are guided by document query terms of the search query set object parameter that are initially optimized by assessment means, scoring means, stochastic means, and organizing means that lead to selective variations, constructive variations, clustering variations, and stochastic variations of the parameter sets. The global optimization of parameter sets leads to stochastically improvements to all object parameters by selective variations, constructive variations, clustering variations, and stochastic variations.