Systems and methods to determine and utilize conceptual relatedness between natural language sources

A microprocessor executable method to ascertain relatedness between information sources, the microprocessor executable method comprising:

• converting natural language of a first information source to a first concept vector, wherein converting natural language of a first information source to a first concept vector includes processing the first information source within a lexical semantic characterization, and further wherein the concept vector is a concept-based representation of at least a portion of the first information source;
• converting natural language of a second information source to at least one second concept vector, wherein converting natural language of a second information source to a second concept vector includes processing the second information source within a lexical semantic characterization, and further wherein the concept vector is a concept-based representation of at least a portion of the second information source;
• ontologically corn paring the at least one second concept vector with a concept knowledge database;
• producing a second order concept vector from the ontologically compared at least one second concept vector;
• determining a similarity between the first concept vector and the second order concept vector;
• and
• calculating a metric of the similarity.

A microprocessor executable system configured to ascertain relatedness between information sources, the microprocessor executable method comprising:

• a storage medium configured to store natural language of a first information source and a second information source;
• and
• a processor configured to execute instructions to convert the natural language of the first information source to a first concept vector, wherein converting natural language of a first information source to a first concept vector includes processing the first information source within a lexical semantic characterization, and further wherein the concept vector is a concept-based representation of at least a portion of the first information source, and to convert the natural language of the second information source to a second concept vector, wherein converting natural language of a second information source to a second concept vector includes processing the second information source within a lexical semantic characterization, and further wherein the concept vector is a concept-based representation of at least a portion of the second information source;
• and determine at least one similarity between the first concept vector and the second concept vector;
• and calculate a metric of the at least one similarity.