At present, the algorithms about semantic similarity of
precise ontology are usually divided into three categories
[12]: (1) Concept name based, that is, according to
English morphology structure, two similar words are
considered as having the same meaning. Representative
algorithms are Edit-distance method and Dictionarybased
method, these algorithms are simple and fast, but
the environmental factor impacts on semantic information
are not taken into considerations. (2) Concept instance
based, that is, the joint distribution of common instances
between concepts is computed using statistical probability.
Representative algorithms are Glue method and Jaccard
method, and these algorithms have high fitness for
particular systems, but depend on the quality of training
set. (3) Concept structure based, that is, based on the
extracting of attributes in concept and rule relation graph
and the assigning of weights, the semantic distance is
calculated. Representative algorithms are Rada method
and Sycara method, these algorithms are widely used, but
the implicit connections of rough concepts in the real
world are not involved