This book constitutes the revised selected papers from the 5th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2015, held in Vienna, Austria in December 2015. The 8 papers presented in this volume were carefully reviewed and selected from 22 submissions. They cover theoretical issues related to process representation, discovery and analysis, or provide practical and operational experiences in process discovery and analysis. They focus mainly on the adoption of process mining algorithms in conjunction and coordination with other techniques and methodologies.

This book constitutes the thoroughly refereed proceedings of the First International Symposium on Data-Driven Process Discovery and Analysis held in Campione d'Italia, Italy, in June/July 2011. The 11 revised full papers were carefully selected from 31 submissions. In addition to the thorough review process, the lively discussions at the event itself also helped the authors to improve their papers and to foster interesting extensions. The selected papers cover a wide range of topics spanning from theoretical issues related to process representation to practical experience in process discovery and analysis.

This book constitutes the thoroughly refereed proceedings of the Second International Symposium on Data-Driven Process Discovery and Analysis held in Campione d'Italia, Italy, in June 2012. The six revised full papers were carefully selected from 17 submissions. To improve the quality of the contributions the symposium fostered the discussion during the presentation, giving authors the opportunity to improve their work extending the presented results. The selected papers cover topics spanning from theoretical issues related to process representation, discovery and analysis to practical and operational experiences in process discovery and analysis.

This book constitutes the revised selected papers from the 6th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2016, held in Graz, Austria in December 2016. The 5 papers presented in this volume were carefully reviewed and selected from 18 submissions. In this edition, the presentations focused on the adoption of process mining algorithms for continuous monitoring of business process. They underline the most relevant challenges identified and propose novel solutions for their resolution.

This book constitutes the thoroughly refereed proceedings of the Third International Symposium on Data-Driven Process Discovery and Analysis held in Riva del Garda, Italy, in August 2013. The six revised full papers were carefully selected from 18 submissions. Following the event, authors were given the opportunity to improve their papers with the insights they gained from the symposium. The selected papers cover theoretical issues related to process representation, discovery and analysis or provide practical and operational experiences in process discovery and analysis.

This book constitutes revised selected papers from the 8th and 9th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2018, held in Seville, Spain, on December 13–14, 2018, and SIMPDA 2019, held in Bled, Slovenia, on September 8, 2019. From 16 submissions received for SIMPDA 2018 and 9 submissions received for SIMPDA 2019, 3 papers each were carefully reviewed and selected for presentation in this volume. They cover theoretical issues related to process representation, discovery, and analysis or provide practical and operational examples of their application.

This book constitutes the revised selected papers from the 7th IFIP WG 2.6 International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2017, held in Neuchatel, Switzerland, in December 2017. The 6 papers presented in this volume were carefully reviewed and selected from 19 submissions. They cover theoretical issues related to process representation, discovery, and analysis or provide practical and operational examples of their application.

This book constitutes the proceedings of the 12th International Conference on Business Process Management, BPM 2014, held in Haifa, Israel, in September 2014. The 21 regular papers and 10 short papers included in this volume were carefully reviewed and selected from 123 submissions. The papers are organized in 9 topical sections on declarative processes, user-centered process approaches, process discovery, integrative BPM, resource and time management in BPM, process analytics, process enabled environments, discovery and monitoring, and industry papers.

This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics. After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges. Overall, this book provides a comprehensive overview of the state of the art in process mining. It is intended for business process analysts, business consultants, process managers, graduate students, and BPM researchers.

These are the proceedings of the tenth event of the Industrial Conference on Data Mining ICDM held in Berlin (www.data-mining-forum.de). For this edition the Program Committee received 175 submissions. After the pe- review process, we accepted 49 high-quality papers for oral presentation that are included in this book. The topics range from theoretical aspects of data mining to app- cations of data mining such as on multimedia data, in marketing, finance and telec- munication, in medicine and agriculture, and in process control, industry and society. Extended versions of selected papers will appear in the international journal Trans- tions on Machine Learning and Data Mining (www.ibai-publishing.org/journal/mldm). Ten papers were selected for poster presentations and are published in the ICDM Poster Proceeding Volume by ibai-publishing (www.ibai-publishing.org). In conjunction with ICDM four workshops were held on special hot applicati- oriented topics in data mining: Data Mining in Marketing DMM, Data Mining in LifeScience DMLS, the Workshop on Case-Based Reasoning for Multimedia Data CBR-MD, and the Workshop on Data Mining in Agriculture DMA. The Workshop on Data Mining in Agriculture ran for the first time this year. All workshop papers will be published in the workshop proceedings by ibai-publishing (www.ibai-publishing.org). Selected papers of CBR-MD will be published in a special issue of the international journal Transactions on Case-Based Reasoning (www.ibai-publishing.org/journal/cbr).