Abstract: An analytical method and apparatus is provided for analyzing and interpreting signals from unstructured data to identify and reason about underlying concepts. The method and apparatus include functions of generating qualitative and quantitative representations of explicit semantic concepts and implicit related or associated concepts, and defining a Semantic Boundary Index used for real-time processing of unstructured data fields or streams in a manner that characterizes, stores, measures, monitors, enables transactional updates or analyses of implicit and explicit information or evidence to identify explicit and implicit or hidden semantic concept, the semantic boundary index being produced by dynamic partitioning through semiotic-based signal processing. The semiotic-based signal processing occurs through agent-based dynamic sensing, characterizing, storing, monitoring, reasoning about and partitioning of unstructured data into core semantic elements.

Abstract: Described herein is a method and system of geometrically encoding data including partitioning data into a plurality of semantic classes based on a dissimilarity metric, generating a subspace formed by first and second data elements, the first and second data elements being included in first and second numbers of partitioned semantic classes, encoding the first data element with respect to the second data element such that the generated subspace formed by the first data element and the second data element is orthogonal, computing a weight distribution of the first data element with respect to the second data element, the weight distribution being performed for each of the first number of semantic classes and the second number of semantic classes, and determining a dominant semantic class corresponding to an ordered sequence of the first data element and the second data element, the dominant semantic class having a maximum weight distribution.

Abstract: A method and apparatus is provided for implementing combinatorial hypermaps (CHYMAPS) and/or generalized combinatorial maps (G-Maps) based data representations and operations, comprising: mapping term-algebras to tree-based numbers using a fast algorithm and representing a graph of the mapping structure as a CHYMAPS using reversible numeric encoding and decoding; generating a representation of CHYMAPS in a form optimized for sub-map (sub-graph) to map (graph) isomorphism and partial matching with a general matching process; performing operations on the CHYMAPS as operations on respective numerical representations; performing compression and decompression using a three bit self-delimiting binary code; and storing and retrieving codes.

Abstract: The invention provides a fast approximate as well as exact hierarchical network storage and retrieval system and method for encoding and indexing graphs or networks into a data structure called the Cognitive Signature for property based, analog based or structure or sub-structure based search. The system and method produce a Cognitive Memory from a multiplicity of stored Cognitive Signatures and are ideally suited to store and index all or parts of massive data sets, linguistic graphs, protein graphs, chemical graphs, graphs of biochemical pathways, image or picture graphs as well as dynamical graphs such as traffic graphs or flows and motion picture sequences of graphs. The system and method have the advantage that properties of the Cognitive Signature of the graph can be used in correlations to the properties of the underlying data making the system ideal for semantic indexing of massive scale graph data sets.