计算机科学 ›› 2022, Vol. 49 ›› Issue (11A): 211000001-6.doi: 10.11896/jsjkx.211000001
林文祥, 刘德生
LIN Wen-xiang, LIU De-sheng
摘要: 随着信息技术和网络技术的迅猛发展及其在军事领域的广泛应用,网络信息体系应运而生。网络信息体系以信息为主导,主要的表现为其内含的信息活动流程。信息活动流程的合理性、高效性,直接影响信息在作战体系中的作战效能。采用流程挖掘技术从信息活动事件日志中发现信息活动流程模型,可为信息活动流程的建模、检验和增强提供有效支持。简单通过事件频率分析过滤日志中的噪声,容易导致有效低频路径丢失,降低挖掘的信息活动流程的准确性。结合军事信息活动的特殊性和信息传递的有效性特征,提出了一种基于结构聚合度的有效低频路径挖掘算法。仿真分析表明,该方法可成功分离日志噪声和有效低频路径,对挖掘真实有效的信息流程具有重要意义。
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[1]VAN DER AALST W M P,WEIJTERS T,MARUSTER L.Workflow mining:discovering process models from event logs [J].IEEE Transactions on Knowledge and Data Engineering,2004,16(9):1128-1142. [2]SURIADI S,ANDREWS R,TER HOFSTEDE A,et al.Event log imperfection patterns for process mining:Towards a systematic approach to cleaning event logs[J].Information Systems,2017(64):132-150. [3]FMANNHARDT,MD LEONI,REIJERS H A,et al.Data-Driven Process Discovery-Revealing Conditional Infrequent Behavior from Event Logs[C]//International Conference on Advanced Information Systems Engineering.Cham:Springer,2017. [4]CHEN Q,LU Y,POONS K.An Algorithm to Preserve Infre-quent Relations in Process Mining[C]//Application to Lab Tests Ordering Process.2020. [5]WANG L L,FANG X W,ASARE E,et al.An Optimization Approach for Mining of Process Models with Infrequent Behaviors Integrating Data Flow and Control Flow[J].Scientific Programming,2021(1):1-17. [6]CHAPELA-CAMPA D,MUCIENTES M,LAMAM.Discove-ring infrequent behavioral patterns in process models[C]//International Conference on Business Process Management.Cham:Springer,2017:324-340. [7]LEEMANS S J J,FAHLAND D,VAN DER AALST W M P.Discovering block-structured process models from event logs-a constructive approach[C]//International conference on applications and theory of Petri nets and concurrency.Cham:Springer,2013:311-329. [8]VAN ZELST S J,VAN DONGEN B F,VAN DER AALST W M P,et al.Discovering Relaxed Sound workflow nets using integer linear programming[J].Computing,2018,100(5):529-556. [9]GAO Y N,FANG X W,WANG L L.Business process configuration optimization analysis based on behavioral tightness of Petri nets[J].Computer Science,2017,44(S1):539-542. [10]CHAPELA-CAMPA D,MUCIENTES M,LAMA M.Simplifi-cation of complex process models by abstracting infrequent behaviour[C]//International Conference on Service-Oriented Computing.Cham:Springer,2019:415-430. [11]GOEDERTIER S,MARTENS D,VANTHIENENJ,et al.Robust process discovery with artificial negative events[J].Journal of Machine Learning Research,2009,10:1305-1340. [12]PONCE-DE-LEÓN H,CARMONA J,VANDEN BROUCKESK L M.Incorporating negative information in process discovery[C]//International Conference on Business Process Management.Cham:Springer,2016:126-143. [13]ZHANG Y,LIU Y D,JI Z.Vector similarity measurementmethod[J].Acoustics Technology,2009,28(4):532-536. |
[1] | 白雪骢,朱焱. 一种基于禁忌搜索算法的流程挖掘方法 Process Mining Approach Based on Tabu Search Algorithm 计算机科学, 2016, 43(4): 214-218. https://doi.org/10.11896/j.issn.1002-137X.2016.04.044 |
[2] | 景波,刘莹,陈耿. 基于Petri网的数据库日志分析方法研究 Research on Database Log Based on Petri Nets 计算机科学, 2014, 41(6): 250-253. https://doi.org/10.11896/j.issn.1002-137X.2014.06.049 |
[3] | 马慧 汤庸 吴凌坤. 流程增量挖掘中的模型更新方法 计算机科学, 2009, 36(5): 154-157. |
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