Case - based reasoning ( CBR ) is one of the emerging paradigms for designing intelligent systems . Retrieval of similar cases is a primary step in CBR , and the similarity measure plays a very important role in case retrieval . Sometimes CBR systems are called similarity searching systems , the most important characteristic of which is the effectiveness of the similarity measure used to quantify the degree of resemblance between a pair of cases . This article focuses on the similarity measuring methods for CBR and comprises two parts . The first part reviews the existing methods for measuring similarity in the literature based on more than 100 CBR project studies and some general similarity measures seen in other applications . In the second part , a hybrid similarity measure is proposed for comparing cases with a mixture of crisp and fuzzy features . Its application to the domain of failure analysis is illustrated .