Name: Conformance Checking and Diagnosis in Process Mining: Comparing Observed and Modeled Processes (en Inglés)
Price: 270.17 PEN
Availability: InStock
Author: Munoz-Gama, Jorge
ISBN: 9783319494500

portada Conformance Checking and Diagnosis in Process Mining: Comparing Observed and Modeled Processes (en Inglés)

Formato

Libro Físico

Autor

Jorge Munoz-Gama

Editorial

Springer

Idioma

Inglés

N° páginas

202

Encuadernación

Tapa Blanda

Dimensiones

23.4 x 15.6 x 1.2 cm

Peso

0.31 kg.

ISBN13

9783319494500

Categorías

Gestión del conocimiento empresarial
Data mining: minería de datos
Ciencias de la computación

Conformance Checking and Diagnosis in Process Mining: Comparing Observed and Modeled Processes (en Inglés)

Jorge Munoz-Gama (Autor) · Springer · Tapa Blanda

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Reseña del libro "Conformance Checking and Diagnosis in Process Mining: Comparing Observed and Modeled Processes (en Inglés)"

Process mining techniques can be used to discover, analyze and improve real processes, by extracting models from observed behavior. The aim of this book is conformance checking, one of the main areas of process mining. In conformance checking, existing process models are compared with actual observations of the process in order to assess their quality. Conformance checking techniques are a way to visualize the differences between assumed process represented in the model and the real process in the event log, pinpointing possible problems to address, and the business process management results that rely on these models. This book combines both application and research perspectives. It provides concrete use cases that illustrate the problems addressed by the techniques in the book, but at the same time, it contains complete conceptualization and formalization of the problem and the techniques, and through evaluations on the quality and the performance of the proposed techniques. Hence, this book brings the opportunity for business analysts willing to improve their organization processes, and also data scientists interested on the topic of process-oriented data science.