System and method for text categorization based on ontologies

1. A system for text categorization based on ontologies, the system comprising:

a plurality of data collector software modules stored and operating on a plurality of network-attached computers;

a categorizer software module stored and operating on a network-attached server computer; and

a database server comprising an indexed database of documents and their categorizations, and further comprising a plurality of ontologies, each ontology comprising a plurality of hierarchical taxonomies and each hierarchical taxonomy comprising a plurality of taxons;

wherein the data collector software modules receive a text to be classified and submits the received text to the categorizer software module; and

further wherein the categorizer performs the following steps to categorize the received text:

splitting the text into sentences;

selecting words or phrases from the sentences of the received text that are present in one or more of the plurality of ontologies stored in the database server;

determining one or more specific subcategories that the sentence corresponds to in view of pattern analysis of the selected words or phrases;

selecting a plurality of subtrees from the plurality of ontologies based on the determination of the selected words or phrases belonging to one or more specific subcategories;

determining a weight for each subcategory within the one or more of the specific subcategories;

using the selected plurality of subtrees to create at least one modified subtree by eliminating from the selected plurality of subtrees subcategories having a category weight below a threshold;

for each of the at least one modified subtree, computing a conditionality coefficient to make a Boolean determination of whether to consider the respective modified subtree or not in categorization of the text; and

using any modified subtree that has been determined to be considered in categorization of the text to categorize the text;

wherein the conditionality coefficient is determined at least in part by user-defined rules or the presence, or absence, of diagnostics in nodes of at least one neighboring subtree.

2. A method for text categorization based on ontologies, the method comprising the steps of:

receiving, via a plurality of data collector software modules stored and operating on a plurality of network-attached computers, a text to be classified;

submitting the received text to a categorizer software module stored and operating on a network-attached server computer;

performing the following using the categorizer software module: splitting the text into sentences;

selecting words or phrases from the sentences of the received text that are present in one or more the plurality of ontologies stored in the database server;

determining one or more specific subcategories that the sentence corresponds to in view of pattern analysis of the selected words or phrases;

selecting a plurality of subtrees from the plurality of ontologies based on the determination of the selected words or phrases belonging to one or more specific subcategories;

determining a weight for each subcategory within the one or more of the specific subcategories;

using the selected plurality of subtrees to create at least one modified subtree by eliminating from the selected plurality of subtrees subcategories having a category weight below a threshold;

for each of the at least one of modified subtree, computing a conditionality coefficient;

using the conditionality coefficient to make a Boolean determination of whether to consider the respective modified subtree or not in categorization of the text; and

using any modified subtree that has been determined to be considered to store a resulting document categorization in a database server comprising an indexed database of texts and each of their respective categorizations, and further comprising a plurality of ontologies, each ontology comprising a plurality of hierarchical taxonomies and each hierarchical taxonomy comprising a plurality of taxons;

wherein the conditionality coefficient is determined at least in part by user-defined rules or the presence, or absence, of diagnostics in nodes of at least one neighboring subtree.