Name
Abstract | ||
|---|---|---|
Despite the omnipresence of event logs in transactional information systems (cf. WFM, ERP, CRM, SCM, and B2B systems), historic information is rarely used to analyze the underlying processes. Process mining aims at improving this by providing techniques and tools for discovering process, control, data, organizational, and social structures from event logs, i.e., the basic idea of process mining is to diagnose business processes by mining event logs for knowledge. Given its potential and challenges it is no surprise that recently process mining has become a vivid research area. In this paper, a novel approach for process mining based on two event types, i.e., START and COMPLETE, is proposed. Information about the start and completion of tasks can be used to explicitly detect parallelism. The algorithm presented in this paper overcomes some of the limitations of existing algorithms such as the 驴-algorithm (e.g., short-loops) and therefore enhances the applicability of process mining. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/s10844-007-0052-1 | J. Intell. Inf. Syst. |
Keywords | Field | DocType |
underlying process,business process,novel approach,basic idea,historic information,event log,process mining,event type,mining event log,transactional information system,b2b system,information systems,data mining,information analysis,process control,petri nets | Information system,Data mining,Management information systems,Petri net,Computer science,Correctness,Process modeling,Process control,Completeness (statistics),Process mining | Journal |
Volume | Issue | ISSN |
32 | 2 | 0925-9902 |
ISBN | Citations | PageRank |
0-7695-2925-9 | 38 | 1.87 |
References | Authors | |
27 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Changrui Ren | 1 | 82 | 14.85 |
| Lijie Wen | 2 | 452 | 44.34 |
| jin dong | 3 | 38 | 1.87 |
| Hongwei Ding | 4 | 181 | 31.78 |
| wei wang | 5 | 38 | 1.87 |
| Minmin Qiu | 6 | 49 | 3.68 |