Relativistic concept measuring system for data clustering

A non-transitory computer readable medium having stored thereon a program that when executed by a particularly programmed computing device causes the particularly programmed computing device to execute a method of generating, within a framework that represents data as particles in a vector field, an implicit structure to derive conclusions about data having an implicit ontology, the method comprising:

• obtaining the data having the implicit ontology and being represented at a plurality of data points;
• representing a superposition of the obtained data by a superposition of multiple fields including vector fields based on solutions of respective distance field functions, the representation of the superposition corresponding to a representation of a superposed state, wherein each data point is represented as a particle in the vector fields and the vector fields include one or more concepts also represented as respective particles;
• determining, based on the superposition of the multiple fields, forces at respective data points of the obtained data within the vector fields;
• separating the superposed state by shifting each concept of the obtained data along respective directions of the forces and then updating the superposition of the multiple fields based on the evolved data by re-solving the respective distance field functions with the positions of the shifted concepts;
• for a data point of the data points,
• repeating the separating step until the data point is shifted along the forces and converges to a stable point based on a pre-defined threshold, wherein the repeated shifting generates a path of the data point, and the one of the one or more concepts forms a leaf node in the implicit data structure,
• measuring distances between the data point and concepts positioned along the path of the data point within the separated superposed state, and, for concepts within a clustering threshold distance of the path of the data point, linking the leaf node to nodes of the concepts within the clustering threshold distance as to generate the implicit structure as the implicit ontology,
• storing said implicit ontology and similarity in a memory;
• and
• performing a search of said stored implicit ontology including deriving a similarity of a first piece of the data to a second piece of the data based on the measured distances between the first piece and the second piece in the implicit structure.

A device for generating, within a framework that represents data as particles in a vector field, an implicit structure to derive conclusions about data having an implicit ontology, the device comprising:

• processing circuitry configured to
• obtain the data having the implicit ontology and being represented at a plurality of data points;
• represent a superposition of the obtained data by a superposition of multiple fields including vector fields based on solutions of respective distance field functions, the representation of the superposition corresponding to a representation of a superposed state, wherein each data point is represented as a particle in the vector fields and the vector fields include one or more concepts also represented as respective particles;
• determine, based on the superposition of the multiple fields, forces at respective data points of the obtained data within the vector fields;
• separate the superposed state by shifting each concept of the obtained data along respective directions of the forces and then updating the superposition of the multiple fields based on the evolved data by re-solving the respective distance field functions with the positions of the shifted concepts;
• for a data point of the data points,
• repeat the separating step until the data point is shifted along the forces and converges to a stable point based on a pre-defined threshold, wherein the repeated shifting generates a path of the data point, and the one of the one or more concepts forms a leaf node in the implicit data structure,
• measure distances between the data point and concepts positioned along the path of the data point within the separated superposed state, and, for concepts within a clustering threshold distance of the path of the data point, linking the leaf node to nodes of the concepts within the clustering threshold distance as to generate the implicit structure as the implicit ontology;
• and
• store said implicit ontology and similarity in a memory;
• and
• perform a search of said stored implicit ontology including deriving a similarity of a first piece of the data to a second piece of the data based on the measured distances between the first piece and the second piece in the implicit structure.