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MAKO: Multi-Ontology Analytical Knowledge Organization based on Topic Maps
Paper, was published by Larry Kerschberg and Riki Morikawa at 2003-09-30
External Links: download paper and IEEE record
This paper addresses how the XML Topic Map (XTM) 1.0 standard can be used to develop an analytical knowledge base comprised of multiple ontologies to support intelligence assessments. Termed the Multi-Ontology Analytical Knowledge Organizational (MAKO) framework, it incorporates a Multidimensional Ontology Model (MOM) that organizes subjects into separate conceptualizations based upon common-sense groupings. Topic, association and occurrence elements are temporally serialized, according to the Temporal Layer Model (TLM), to accommodate, and historically preserve, modifications to the knowledge base as world events change.
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The idea of Topic Maps is essential to enable dynamic information logistic. This requires a system that understands the context of the user to provide relevant informations and options automatically. Therefore semantic analysis is needed organizing content in a dynamic net structure.