發(fā)布時間：2018-05-30 02:20

  本文選題：BPMN + .模型　； 參考：《計算機研究與發(fā)展》2017年09期

【摘要】：符合性檢測方法作為比較和關(guān)聯(lián)事件日志與流程模型的技術(shù),是三大核心流程挖掘技術(shù)之一,可用于量化符合性和診斷偏差.BPMN 2.0模型具有豐富的表達(dá)能力,能夠表達(dá)多實例、子流程、邊界事件、OR網(wǎng)關(guān)等多種復(fù)雜模式,但是目前還沒有針對這些復(fù)雜模式的BPMN 2.0模型符合性檢測算法.針對該問題,提出了基于對齊的BPMN 2.0模型符合性檢測算法Acorn,該算法支持上述多種復(fù)雜模式.在深入分析BPMN 2.0模型中多種復(fù)雜模式的具體語義并分析其具體使能情況的基礎(chǔ)上,Acorn算法引入對齊操作,利用A*搜索算法尋找到代價最小的匹配軌跡,同時引入虛擬代價和預(yù)估代價來對A*算法進(jìn)行搜索空間的優(yōu)化,最后根據(jù)最佳匹配軌跡來計算模型與日志的契合度.實驗表明,Acorn算法能夠正確有效地計算帶有復(fù)雜模式的BPMN 2.0模型與日志之間的契合度,且虛擬代價和預(yù)估代價的引入,大大減少了搜索空間,有效提高了算法的運行速度.
[Abstract]:As a technique of comparing and associating event log and process model, conformance detection method is one of the three core process mining techniques. It can be used to quantify compliance and diagnose deviation. BPMN 2.0 model has rich expression ability and can express many examples. There are many complex patterns such as sub-flow, boundary event OR gateway and so on, but there is no BPMN 2.0 model conformance detection algorithm for these complex patterns. In order to solve this problem, an alignment based BPMN 2.0 model conformance detection algorithm (Acorn) is proposed, which supports many complex patterns mentioned above. On the basis of deep analysis of the semantics of many complex patterns in the BPMN 2.0 model and the analysis of its specific enabling situation, this paper introduces alignment operations into the Acorn algorithm, and uses the A * search algorithm to find the least costly matching locus. At the same time, the virtual cost and the estimated cost are introduced to optimize the search space of the A * algorithm. Finally, the consistency between the model and the log is calculated according to the optimal matching trajectory. The experimental results show that the algorithm can correctly and effectively calculate the consistency between the BPMN 2.0 model with complex schema and the log, and the introduction of virtual cost and prediction cost greatly reduces the search space and effectively improves the running speed of the algorithm.
【作者單位】： 清華大學(xué)軟件學(xué)院;首都經(jīng)濟(jì)貿(mào)易大學(xué)信息學(xué)院;
【基金】：國家重點研發(fā)計劃項目(2016YFB1001101) 國家自然科學(xué)基金項目(61472207,61325008,61402301)~~
【分類號】：TP301.6
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本文編號：1953485