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Process Querying Methods (Hardcover, 1st ed. 2022)
Loot Price: R3,181
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Process Querying Methods (Hardcover, 1st ed. 2022)
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This book presents a framework for developing as well as a
comprehensive collection of state-of-the-art process querying
methods. Process querying combines concepts from Big Data and
Process Modeling and Analysis with Business Process Intelligence
and Process Analytics to study techniques for retrieving and
manipulating models of real-world and envisioned processes to
organize and extract process-related information for subsequent
systematic use. The book comprises sixteen contributed chapters
distributed over four parts and two auxiliary chapters. The
auxiliary chapters by the editor provide an introduction to the
area of process querying and a summary of the presented methods,
techniques, and applications for process querying. The introductory
chapter also examines a process querying framework. The contributed
chapters present various process querying methods, including
discussions on how they instantiate the framework components, thus
supporting the comparison of the methods. The four parts are due to
the distinctive features of the methods they include. The first
three are devoted to querying event logs generated by IT-systems
that support business processes at organizations, querying process
designs captured in process models, and methods that address
querying both event logs and process models. The methods in these
three parts usually define a language for specifying process
queries. The fourth part discusses methods that operate over inputs
other than event logs and process models, e.g., streams of process
events, or do not develop dedicated languages for specifying
queries, e.g., methods for assessing process model similarity. This
book is mainly intended for researchers. All the chapters in this
book are contributed by active researchers in the research
disciplines of business process management, process mining, and
process querying. They describe state-of-the-art methods for
process querying, discuss use cases of process querying, and
suggest directions for future work for advancing the field. Yet,
also other groups like business or data scientists and other
professionals, lecturers, graduate students, and tool vendors will
find relevant information for their distinctive needs. Chapter
"Celonis PQL: A Query Language for Process Mining" is available
open access under a Creative Commons Attribution 4.0 International
License via link.springer.com.
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