We can all close up shop now. Our good buddy Werner Ceusters
has solved all the problems of ontology and NLP and submitted
patents for the solutions. See below. (01)
John
__________________________________________________________________ (02)
http://www.freepatentsonline.com/y2013/0030827.html (03)
Title:
Semantic Interoperability System for Medicinal Information
Document Type and Number:
United States Patent Application 20130030827
Kind Code: A1 (04)
Abstract:
A system for managing and exchanging electronic information provides a
rules management component for executing conceptual rules, an ontology
management component, an information model management component, and a
system configuration management component. The ontology management
component manages at least one ontology and mappings between members of
different ontologies. The ontologies may include a code system and a
terminology. The ontology management component may manage a value set
that is a subset of the terminology. The information model management
component manages one or more information model schemas, each defining
an information model and comprising information defining at least one
slot within the information model. The system configuration management
component manages configuration information on the configuration of each
system component. The system configuration component utilizes services
of the rules management component, information model management
component and ontology management component to dynamically bind value
sets to slots of the information model. (05)
__________________________________________________________________ (06)
http://www.freepatentsonline.com/y2009/0259459.html (07)
Title:
CONCEPTUAL WORLD REPRESENTATION NATURAL LANGUAGE UNDERSTANDING SYSTEM
AND METHOD
United States Patent Application 20090259459
Kind Code: A1 (08)
Abstract:
A Natural Language Understanding system is provided for indexing of free
text documents. The system according to the invention utilizes
typographical and functional segmentation of text to identify those
portions of free text that carry meaning. The system then uses words and
multi-word terms and phrases identified in the free to text to identify
concepts in the free text. The system uses a lexicon of terms linked to
a formal ontology that is independent of a specific language to extract
concepts from the free text based on the words and multi-word terms in
the free text. The formal ontology contains both language independent
domain knowledge concepts and language dependent linguistic concepts
that govern the relationships between concepts and contain the rules
about how language works. The system according to the current invention
may preferably be used to index medical documents and assign codes from
independent coding systems, such as, SNOMED, ICD-9 and ICD-10. The
system according to the current invention may also preferably make use
of syntactic parsing to improve the efficiency of the method. (09)
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