基于概率分布的流程工厂模型拓扑相似度计算
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摘要
为了解决流程工厂模型拓扑相似度计算问题,提出基于概率分布函数的相似度计算方法.首先利用隐马尔可夫建模及状态序列推断,从工厂拓扑结构中挖掘隐含的拓扑语义;然后通过隐含狄利克雷分配模型将拓扑语义映射成长度固定的特征向量;最后用概率模型描述全体特征向量分布,并用分布函数计算2个拓扑结构间的相似度.依据流程工厂专家设计建模的专业知识及从业经验,验证了该方法的准确性和有效性.
To solve the problem of topology similarity calculation of process plant models, a similarity calculation method based on cumulative distribution function has been presented. Firstly, the method mines the underlying topology semantic from topology structure through HMM modeling and state sequences reference; then with the LDA model, the topology semantic is mapped to length fixed feature vector; finally, all the feature vectors are described by a probabilistic model and the similarity between two topology structures is calculated based on the cumulative distribution function. According to the specialized knowledge and experiences from process plant professionals of model designing and modeling, the accuracy and effectiveness of the presented method is verified.
To solve the problem of topology similarity calculation of process plant models, a similarity calculation method based on cumulative distribution function has been presented. Firstly, the method mines the underlying topology semantic from topology structure through HMM modeling and state sequences reference; then with the LDA model, the topology semantic is mapped to length fixed feature vector; finally, all the feature vectors are described by a probabilistic model and the similarity between two topology structures is calculated based on the cumulative distribution function. According to the specialized knowledge and experiences from process plant professionals of model designing and modeling, the accuracy and effectiveness of the presented method is verified.
引文
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[2]Wen R,Tang W Q,Su Z Y.Topology based 2D engineering drawing and 3D model matching for process plant[J].Graphical Models,2017,92:1-15
[3]Deza M M,Deza E.Dictionary of distances[M].Amsterdam:Elsevier Press,2006:62-80
[4]Cha S H.Comprehensive survey on distance/similarity measures between probability functions[J].International Journal of Mathematical Models and Methods in Applied Sciences,2007,1(4):300-307
[5]Zahoranszky-Kohalmi G,Bologa C G,Oprea T I.Impact of similarity threshold on the topology of molecular similarity networks and clustering outcomes[J].Journal of Cheminformatics,2016,8(1):Article No.16
[6]Gera R,Alonso L,Crawford B,et al.Identifying network structure similarity using spectral graph theory[J].Applied Network Science,2018,3(1):Article No.2
[7]Zhang S,Zheng X F,Hu C J.A survey of semantic similarity and its application to social network analysis[C]//Proceedings of the IEEE International Conference on Big Data.Los Alamitos:IEEE Computer Society Press,2015:2362-2367
[8]Rawashdeh A,Ralescu A L.Similarity measure for social networks-a brief survey[C]//Proceedings of the 26th Modern AIand Cognitive Science Conference.North Carolina:MAICSPress,2015:153-159
[9]Labriji A,Charkaoui S,Abdelbaki I,et al.Similarity measure of graphs[J].International Journal of Recent Contributions from Engineering,Science&IT,2017,5(2):42-56
[10]Yan J C,Yin X C,Lin W Y,et al.A short survey of recent advances in graph matching[C]//Proceedings of the ACM on International Conference on Multimedia Retrieval.New York:ACM Press,2016:167-174
[11]Hong L,Zhou L,Lian X,et al.Subgraph matching with set similarity in a large graph database[J].IEEE Transactions on Knowledge and Data Engineering,2015,27(9):2507-2521
[12]Dijkman R,Dumas M,Garcia-Banuelos L.Graph matching algorithms for business process model similarity search[C]//Proceedings of the 7th International Conference on Business Process Management.Berlin:Springer-Verlag Press,2009:48-63
[13]Koutra D,Parikh A,Ramdas A,et al.Algorithms for graph similarity and subgraph matching[OL].[2018-02-25].http://www.cs.cmu.edu/~jingx/docs/DBreport.pdf
[14]Conte A,de Virgilio R,Maccioni A,et al.Finding all maximal cliques in very large social networks[C]//Proceedings of the19th International Conference on Extending Database Technology.Konstanz:OpenProceedings.org Press,2016:173-184
[15]Melnik S,Garcia-Molina H,Rahm E.Similarity flooding:a versatile graph matching algorithm and its application to schema matching[C]//Proceedings of the 18th International Conference on Data Engineering.Los Alamitos:IEEE Computer Society Press,2002:117-228
[16]Zhang J,Yuan C F,Huang Y H.Parallelized similarity flooding algorithm for processing large scale graph datasets with mapreduce[C]//Proceedings of the 13th International Conference on Parallel and Distributed Computing,Applications and Technologies.Los Alamitos:IEEE Computer Society Press,2012:184-188
[17]Jeh G,Widom J.SimRank:a measure of structural-context similarity[C]//Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.New York:ACM Press,2002:538-543
[18]Zager L A,Verghese G C.Graph similarity scoring and matching[J].Applied Mathematics Letters,2008,21(1):86-94
[19]Bayati M,Gleich D F,Saberi A,et al.Message-passing algorithms for sparse network alignment[J].ACM Transactions on Knowledge Discovery from Data,2013,7(1):Article No.3
[20]Sun Z G,Huo H W,Chen X Y.Fast top-k graph similarity search via representative matrices[J].IEEE Access,2018,6:21408-21417
[21]Parimala B M,Lopez D,Gao X Z.Graph clustering using k-neighbourhood attribute structural similarity[J].Applied Soft Computing,2016,47:216-223
[22]Venturini M,Alejandro G.Statistical distances and probability metrics for multivariate data,ensembles and probability distributions[D].Madrid:Charles III University of Madrid,2015
[23]Hershey J R,Olsen P A.Approximating the Kullback-Leibler divergence between Gaussian mixture models[C]//Proceedings of the IEEE International Conference on Acoustics,Speech and Signal Processing.Los Alamitos:IEEE Computer Society Press,2007,4:317-320
[24]Murphy K P.Machine learning:a probabilistic perspective[M].Cambridge:MIT Press,2012
[25]Blei D M,Ng A Y,Jordan M I.Latent Dirichlet allocation[J].Journal of Machine Learning Research,2003,3:993-1022
[26]Jelodar H,Wang Y,Yuan C,et al.Latent Dirichlet allocation(LDA)and topic modeling:models,applications,a survey[OL].[2018-02-25].https://arxiv.org/ftp/arxiv/papers/1711/1711.04305.pdf
[27]Bishop C M.Pattern recognition and machine learning[M].Heidelberg:Springer Press,2007:74-136