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Efficient business process consolidation: combining topic features with structure matching
TLDR
This paper presents an approach to automating business process consolidation by applying process topic clustering based on business process libraries, using a graph mining algorithm to extract process patterns, identifying frequent subgraphs under the same process topic, filling the pertinent subgraph information into a table of frequent process subGraphs, and finally merging these frequentsubgraphs to obtain merged business processes using a process merging algorithm. Expand
  • 21
A self-feedback strategy differential evolution with fitness landscape analysis
TLDR
This paper presents a new self-feedback strategy differential evolution (SFSDE) algorithm based on fitness landscape analysis of single-objective optimization problem. Expand
  • 7
Business Process Consolidation Based on E-RPSTs
TLDR
This paper describes the concept of workflow merge and methods for merging business processes. Expand
  • 2
Building business process ontology based on concept hierarchy model
TLDR
This paper proposes an approach for ontology extraction on business process by incorporating concept hierarchy as background knowledge. Expand