Text mining for real time ontology evolution

Abstract

In this paper we propose the novel technique, On-line Contin-uous Ontological Evolution (OCOE) approach, which applies text mining to automate TCM (Traditional Chinese Medicine) telemedicine ontology evolution. The first step of the automation process is opening up a closed skeletal TCM ontology core (TCM onto-core) for continuous evolution and absorption of new scientific knowledge. The test-bed for the OCOE verification was the production TCM telemedicine system of the Nong's Company Limited; Nong's is a subsidiary of the PuraPharm Group in the Hong Kong SAR, which is dedicated to TCM telemedicine system development. At Nong's the skeletal TCM onto-core for clinical practice is closed (does not automatically evolve). When the OCOE is combined with the Nong's enterprise TCM onto-core it: i) invokes its text miner by default to search for new scientific findings over the open web incessantly; and ii) selectively prunes and stores useful new findings in special OCOE data structures. These data structures can be appended to the skeletal TCM onto-core logically to catalyze the evolution of the overall system TCM ontology, which is the logical combination: 'original skeletal TCM onto-core plus contents of the special OCOE data structures' The evolutionary process works on the contents of the OCOE data structures only and does not alter any skeletal TCM onto-core knowledge. This onto-core evolution approach is called the 'logical-knowledge-add-on' technique. OCOE deactivation will nullify the pointers and cut the association between the OCOE data structures and skeletal TCM onto-core, thus immediately reverting the clinical practice back to the original skeletal TCM onto-core basis.