Download Data-Driven Process Discovery and Analysis: 4th by Paolo Ceravolo, Barbara Russo, Rafael Accorsi PDF

By Paolo Ceravolo, Barbara Russo, Rafael Accorsi

This booklet constitutes the completely refereed complaints of the Fourth foreign Symposium on Data-Driven method Discovery and research held in Riva del Milan, Italy, in November 2014.

The 5 revised complete papers have been rigorously chosen from 21 submissions. Following the development, authors got the chance to enhance their papers with the insights they won from the symposium. in this version, the displays and discussions often fascinated with the implementation of method mining algorithms in contexts the place the analytical technique is fed through facts streams. the chosen papers underline the main appropriate demanding situations pointed out and suggest novel recommendations and techniques for his or her solution.

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Additional info for Data-Driven Process Discovery and Analysis: 4th International Symposium, SIMPDA 2014, Milan, Italy, November 19-21, 2014, Revised Selected Papers

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A SUBMITTED+COMPLETE ⎪ ⎪ ⎪ A PARTLYSUBMITTED+COMPLETE ⎪ ⎪ ⎨ Activities A PREACCEPTED+COMPLETE W Complementeren aanvraag+SCHEDULE and pattern⎪ ⎪ ⎪ ⎪ ⎪ W Complementeren aanvraag+START ⎩ A DECLINED+COMPLETE ⎧ Episode Discovery ⎪ ⎪ ⎪ ⎨ α-algorithm [11] Discovery Heuristics miner [14] algorithms⎪ ⎪ ⎪ ⎩ Inductive miner [22] DECLARE miner [23] x x x x x x x x x x + + + + + + + + +a +b +c + +b + + + + +b +c a Indicates the pattern was revealed, but only after increasing maxT raceDist. Indicates the pattern was revealed, but obfuscated by choice constructs.

Springer, Heidelberg (2014) Discovery of Frequent Episodes in Event Logs 31 23. : User-guided discovery of declarative process models. In: 2011 IEEE Symposium on Computational Intelligence and Data Mining (CIDM), pp. 192–199. IEEE (2011) 24. : Efficient discovery of understandable declarative process models from event logs. , Wrycza, S. ) CAiSE 2012. LNCS, vol. 7328, pp. 270–285. Springer, Heidelberg (2012) 25. : A knowledge-based integrated approach for discovering and repairing declare maps. ) CAiSE 2013.

47, 220–243 (2015) 9. : Episode miner. nl/repos/prom/Packages/ EpisodeMiner/. Accessed 9 January 2015 10. : Fast algorithms for frequent episode discovery in event sequences. In: Proceedings of the 3rd workshop on mining temporal and sequential data, SIGKDD, Seattle, WA, USA. , August 2004 11. : Workflow mining: discovering process models from event logs. IEEE Trans. Knowl. Data Eng. 16(9), 1128–1142 (2004) 12. : Workflow mining: current status and future directions. C. ) CoopIS 2003, DOA 2003, and ODBASE 2003.

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