Titlebook: Business Process Management; 12th International C Shazia Sadiq,Pnina Soffer,Hagen V?lzer Conference proceedings 2014 Springer International

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書目名稱Business Process Management影響因子(影響力)




書目名稱Business Process Management影響因子(影響力)學(xué)科排名




書目名稱Business Process Management網(wǎng)絡(luò)公開度




書目名稱Business Process Management網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Business Process Management被引頻次




書目名稱Business Process Management被引頻次學(xué)科排名




書目名稱Business Process Management年度引用




書目名稱Business Process Management年度引用學(xué)科排名




書目名稱Business Process Management讀者反饋




書目名稱Business Process Management讀者反饋學(xué)科排名

Externalize

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與野獸博斗者

Crowd-Based Mining of Reusable Process Model Patterns scale to humans. We demonstrate that if instead the data to mine from are . (not logs), datasets are . (in the order of dozens rather than thousands or millions), and the knowledge to be discovered is . (reusable model patterns), humans outperform computers. We design, implement, run, and test a .

FACT

A Recommender System for Process Discovery dominant algorithm in any of these two disciplines, and then it is often difficult to apply them successfully. Most of these algorithms need a close-to expert knowledge in order to be applied satisfactorily. In this paper, we present a recommender system that uses portfolio-based algorithm selectio

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神刊

A Genetic Algorithm for Process Discovery Guided by Completeness, Precision and Simplicitys, none of the current proposals obtains a good integration between the three objectives and, therefore, the mined models have differences with the real models. In this paper we present a genetic algorithm (ProDiGen) with a hierarchical fitness function that takes into account completeness, precisio

一起

Constructs Competition Miner: Process Control-Flow Discovery of BP-Domain Constructse actual activity workflow is discovered. In most cases their results conform to general purpose representations like Petri nets or Causal nets which are preferred by academic scholars but difficult to comprehend for business analysts. In this paper we propose an algorithm that follows a top-down ap

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