Classifying vague legal concept by using a structural similarity measure based on the fuzzy factor hierarchy

Knowledge representation and similarity measure play an important role in classifying vague legal concepts. In order to consider the fuzziness and context-sensitive effects in knowledge representation, a notion of fuzzy factor hierarchy is studied. The current distance-based and feature-based similarity measures are only surface level ones that, can just make a comparison between objects, and can´t give the context-sensitive effects. A deep level similarity measure: a context-based one, that can evaluate the results of the surface level one is proposed. Further, a structural similarity measure, that is integrated by the surface level and deep level ones, is proposed. A legal argument model, that is based on the proposed knowledge representation and the proposed structural similarity measure, is constructed, by considering the vague legal concept in the United Nations Convention on Contracts for the International Sale of Goods (CISG). The system proposed here is made for the education of law