Computer Science ›› 2014, Vol. 41 ›› Issue (4): 223-229.

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Research on CBR’s Case Representation and Similarity Measure Based on ALCQ(D)

SUN Jin-yong,GU Tian-long,CHANG Liang and MA Lin-wei   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Focused on the lack of qualified number restrictions and concrete domains restrictions in DLs such as EL,ALC,ALCNR that have been used in CBR’s case representation,ALCQ(D) was used with which qualified number restrictions and concrete domains constructor were equipped.First,ALCQ(D) concepts were used to represent and index cases with the requirements of qualified number restrictions,concrete data types and numerical restrictions.Two concrete domain types which are numerical data type and symbolic data type were studied.Second,the normal form of ALCQ(D) was defined to normalize case representations in the form of indexes.Finally the measure method for case similarity was presented,which measures similarities of all parts of the case representations,then weights and summates gained similarities.Experimental results show that ALCQ(D) represents cases more accurately and the measure method for case similarity measures the similarity between cases more adequately.It is very important for increasing the speed of case retrieval,for improving the accuracy of case retrieval,and for improving the efficiency of the CBR system.

Key words: Case-based reasoning(CBR),Description logic(DL),Case representation,Case retrieval,Similarity

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