Crowd-based mining of reusable process model patterns

Carlos Rodríguez, Florian Daniel, Fabio Casati

Результат исследований: Материалы для книги/типы отчетовМатериалы для конференции

5 Цитирования (Scopus)

Аннотация

Process mining is a domain where computers undoubtedly outperform humans. It is a mathematically complex and computationally demanding problem, and event logs are at too low a level of abstraction to be intelligible in large scale to humans. We demonstrate that if instead the data to mine from are models (not logs), datasets are small (in the order of dozens rather than thousands or millions), and the knowledge to be discovered is complex (reusable model patterns), humans outperform computers. We design, implement, run, and test a crowd-based pattern mining approach and demonstrate its viability compared to automated mining. We specifically mine mashup model patterns (we use them to provide interactive recommendations inside a mashup tool) and explain the analogies with mining business process models. The problem is relevant in that reusable model patterns encode valuable modeling and domain knowledge, such as best practices or organizational conventions, from which modelers can learn and benefit when designing own models.

Язык оригиналаАнглийский
Название основной публикацииBusiness Process Management - 12th International Conference, BPM 2014, Proceedings
ИздательSpringer Verlag
Страницы51-66
Число страниц16
Том8659 LNCS
ISBN (печатное издание)9783319101712
DOI
СостояниеОпубликовано - 2014
Опубликовано для внешнего пользованияДа
Событие12th International Conference on Business Process Management, BPM 2014 - Haifa, Израиль
Продолжительность: 7 сен 201411 сен 2014

Серия публикаций

НазваниеLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Том8659 LNCS
ISSN (печатное издание)0302-9743
ISSN (электронное издание)1611-3349

Конференция

Конференция12th International Conference on Business Process Management, BPM 2014
СтранаИзраиль
ГородHaifa
Период7.9.1411.9.14

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Цитировать

    Rodríguez, C., Daniel, F., & Casati, F. (2014). Crowd-based mining of reusable process model patterns. В Business Process Management - 12th International Conference, BPM 2014, Proceedings (Том 8659 LNCS, стр. 51-66). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 8659 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-10172-9_4