基于刻面分类标识和聚类树的构件检索方法
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摘要
针对如何从规模庞大的软件构件库中快速且高效地检索出目标构件的问题,提出一种基于刻面分类标识和聚类树的构件检索方法。使用构件标识集合对构件进行刻面分类标识描述,克服了单纯采用刻面分类法对构件进行分类描述和检索时带来的主观因素的影响;引入聚类树的思想,对构件进行基于语义相似度的聚类分析,建立构件聚类树,能有效地缩小检索范围,减少检索构件与构件库中构件比较的次数,提高检索效率。最后在实验中与一般检索方法对比,实验结果表明该方法的构件查准率为88.3%,查全率为93.1%;而且在大规模的构件库中使用时依然有良好的检索效果。
To quickly and efficiently retrieve the target component from a large software component library,a component retrieval method based on identification of faceted classification and cluster tree was proposed. The component with facet classification identification was described by using the set of component identification,which overcomes the impact of subjective factors when only using facets classification to describe and retrieve components. By introducing cluster tree,the component cluster tree was established by analysis clustering of components based on semantic similarity,thus narrowing the retrieval area,reducing the number of comparisons with component libary,and improving the search efficiency. Finally,the proposed method was experimented and compared with other common retrieval methods. The results show that the precision of the proposed method is 88. 3% and the recall ratio is 93. 1%; moreover,the proposed method also has a good retrieval effect when searching in a large-scale component library.
To quickly and efficiently retrieve the target component from a large software component library,a component retrieval method based on identification of faceted classification and cluster tree was proposed. The component with facet classification identification was described by using the set of component identification,which overcomes the impact of subjective factors when only using facets classification to describe and retrieve components. By introducing cluster tree,the component cluster tree was established by analysis clustering of components based on semantic similarity,thus narrowing the retrieval area,reducing the number of comparisons with component libary,and improving the search efficiency. Finally,the proposed method was experimented and compared with other common retrieval methods. The results show that the precision of the proposed method is 88. 3% and the recall ratio is 93. 1%; moreover,the proposed method also has a good retrieval effect when searching in a large-scale component library.
引文
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[17]王文霞.基于分级策略和聚类索引树的构件检索方法[J].计算机技术与发展,2016,26(4):110-11.(WANG W X.A component retrieval method based on classified policy and cluster index tree[J].Computer Technology and Development,2016,26(4):110-11.)
[2]PRIETO-DAZ R.Implementing faceted classification for software reuse[J].Communications of the ACM,199l,34(5):88-97.
[3]SRINIVAS C,RADHAKRISHNA V,RAO C.Clustering and classification of software component for efficient component retrieval and building component reuse libraries[J].Procedia Computer Science,2014,31(1):1044-1050.
[4]VODITHALA S,PABBOJU S.A dynamic approach for retrieval of software components using genetic algorithm[C]//Proceedings of the 2015 IEEE International Conference on Software Engineering and Service Science.Piscataway,NJ:IEEE,2015:406-410.
[5]DUTTA S,SENGUPTA S.Retrieval of software component version from a software version database:a graph based approach[C]//Proceedings of the 2015 International Conference on Advances in Computer Engineering and Applications.Piscataway,NJ:IEEE,2015:255-259.
[6]王渊峰,张涌,任洪敏,等.基于刻面描述的构件检索[J].软件学报,2002,13(8):1546-1551.(WANG Y F,ZHANG Y,REN H M,et al.Retrieving components based on faceted classification[J].Journal of Software,2002,13(8):1546-1551.)
[7]陆敬筠,宋培钟.领域本体和刻面描述相结合的构件检索研究[J].计算机应用与软件,2013,30(8):36-38.(LU J Y,SONG P Z.On component retrieval method based on the combination of facets description and domain ontology[J].Computer Applications and Software,2013,30(8):36-38.)
[8]张雷,陈立潮,潘理虎,等.构件的标识表示与检索方法研究[J].小型微型计算机系统,2013,34(5):1076-1079.(ZHANG L,CHEN L C,PAN L H,et al.Study on tags representation of components and tags based components retrieval[J].Journal of Chinese Computer Systems,2013,34(5):1076-1079.)
[9]童浩,孙航,李晶,等.基于改进蚁群算法的构件检索方法[J].计算机应用研究,2015,32(7):2057-2059,2064.(TONG H,SUN H,LI J,et al.Method based on improved ant colony algorithm for component retrieving[J].Application Research of Computers,2015,32(7):2057-2059,2064.)
[10]姚全珠,冯欢,田琳,等.基于云端的构件库检索模型[J].计算机应用,2016,36(增刊1):262-264.(YAO Q Z,FENG H,TIAN L,et al.Retrieval model based on cloud component library[J].Journal of Computer Applications,2016,36(Supp1):262-264.)
[11]王映辉.构件式软件技术[M].北京:机械工业出版社,2012:86.(WANG Y H.Component-Based Software Technology[M].Beijing:China Machine Press,2012:86.)
[12]SALTON G,CLEMENT T Y.On the construction of effective vocabularies for information retrieval[C]//SIGPLAN 1973:Proceedings of the 1973 Meeting on Programming Languages and Information Retrieval.New York:ACM,1973:11.
[13]刘大昕,赵磊,王卓,等.一种基于刻面分类和聚类分析的构件分类检索方法[J].计算机应用,2004,24(增刊1):89-90.(LIU D X,ZHAO L,WANG Z,et al.A method of component classification retrieval based on facet classification and cluster analysis[J].Journal of Computer Applications,2004,24(Supp1):89-90.)
[14]YU D T,ZHANG A D.Cluster tree:integration of cluster representation and nearest neighbor search for large datasets with high dimensions[J].IEEE Transections on Knowledge and Data Engineering,2003,15(5):1316-1337.
[15]田晓珍,任姚鹏,王春红,等.一种改进的构件聚类索引树的研究[J].现代计算机,2014(8):12-15,25.(TIAN X Z,REN Y P,WANG C H,et al.Research on an improved component cluster index tree[J].Modern Computer,2014(8):12-15,25.)
[16]RIJSBERGEN C J.Information Retrieval[M].London,UK:Butterworths Press,1979:120.
[17]王文霞.基于分级策略和聚类索引树的构件检索方法[J].计算机技术与发展,2016,26(4):110-11.(WANG W X.A component retrieval method based on classified policy and cluster index tree[J].Computer Technology and Development,2016,26(4):110-11.)