An Application of Fuzzy Theory to the Case-Based Reasoning of the CISG

Abstract

In legal case-based reasoning (CBR), there exist problems concerning fuzziness, e.g., representation of precedents, their retrieval, and similarity measures. In our proposed fuzzy legal CBR system, the issues and features of precedent are characterized on the basis of the facts of precedent and statute rule. The case rule that is used for interpreting the court judgment, which cannot be obtained from the statute rule directly, is made by experts. Fuzziness is represented by membership functions. Features and case rules, written in terms of Compound Predicate Formula (CPF) and frame, are stored in a case base. Cases similar to a new case are retrieved by issues and features, and an inference is made by case rules. A user interface is devised for this system. The system proposed here will be used for law education, where the target law of the system is contract, especially as it relates to the United Nations Convention on Contracts for the International Sale of Goods (CISG).

New weighted fuzzy case retrieval method for customer-driven product design

“…Ever since Zadeh [8] introduced the fuzzy set theory, it has been applied in the product design to describe the complex, uncertain and vague variables. Much case retrieval literature based on fuzzy set has been reported [9][10][11] . These studies advocated using linguistics variables to express the case attributes, and the membership functions, for instance, triangular function, trapezoidal function, and Gaussian function, are chosen for representing linguistics variables to deal with imprecision.…”

Applying a case-based reasoning method for fault diagnosis during maintenance

“…In other words, the CBR system acts primarily as an intelligent associative retrieval system. The following key issues need to be resolved for the construction of a feasible CBR system [ A fuzzy-CBR approach has been proposed to make the CBR system more user-friendly [19,20]. This approach advocates using linguistics variables in fuzzy theory to evaluate the case attributes.…”

“…(a) case representation: how to structure cases and what case features should be stored? A fuzzy-CBR approach has been proposed to make the CBR system more user-friendly [19,20]. This approach advocates using linguistics variables in fuzzy theory to evaluate the case attributes.…”