MeaningFinder 2.2 User's Guide
and Case Studies

MeaningFinder provides an innovative information processing technology based on a patented method for evolutionary transformation of similarity matrices (ETSM).

The main purpose of this release is to introduce the new data processing ideology to the users of computerized methods for intelligent data understanding. Both the ideology and its current software implementation will empower the user’s analytical and discovery potential and will be equally valuable and interesting to any of you who deal with data arrays – whether you are a student, a specialist, a researcher, or a lifelong scholar.

MeaningFinder is not just another tool for data processing – it is your professional partner with strong abilities in searching for and finding the meaning in your data and providing intelligent analytical opinion. It relieves you from the necessity to spend time honing your knowledge in mathematical statistics, seeking adequate equations for your case while looking up, every now and then, all those terms that seem to have been invented to drive you crazy. You will find it a pleasure to watch MeaningFinder performing its duties: processing your data, analyzing, and producing a result that is both logical and non-trivial.

MeaningFinder 2.2 does the following operations: hierarchical clustering of objects in a high-dimensional space (of up to 1000 parameters), accurate identification of objects, high-precision data recognition, extraction of specific target information, graph partitioning, finding correlations, unsupervised tree construction, assessment of a system’s complexity and disorder, identification of sources of chaotic behavior in complex systems, discriminant analysis of parameters, and other related types of analysis.

> Download MeaningFinder 2.2 User's Guide and Case Studies (.pdf) [950 KB]