JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2016, Vol. 46 ›› Issue (2): 22-28.doi: 10.6040/j.issn.1672-3961.1.2015.046

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Design patterns detection based on FCA and CBR

XIAO Zhuoyu1, HE Pei2, YU Bo1, LI Yan3, HU Zhentao1   

  1. 1. Swan College, Central South University of Forestry and Technology, Changsha 410200, Hunan, China;
    2. School of Computer Science &
    Education, Guangzhou University, Guangzhou 510006, Guangdong, China;
    3. Hunan Highway Administration Bureau, Changsha 410209, Hunan, China
  • Received:2015-05-12 Online:2016-04-20 Published:2015-05-12

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Abstract: Aiming to obtain the accurate and reliable detecting model of design patterns that fusion formal concept analysis(FCA)techniques and case cased reasoning(CBR), a novel refinement technique based on more complete software problem description was proposed. Indexes and cases similarity score value was calculated by FCA and Cosine theory. The results of the priority achieved optimal choices, the new knowledge for the retention process phase of the learning model was provided. An approach based on mean average precision(MAP)to assess the performance was proposed. Finally, the experimental results showed that the presented model had more detecting ability in term of MAP comparing to the traditional models.

Key words: case based reasoning, mean average precision, concept lattice, formal concept analysis, design pattern detection, typical feature value

CLC Number: 

  • TP311
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