Antonio Martínez Rojas – författare
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2 produkter
2 produkter
Del 579 - Lecture Notes in Business Information Processing
Automate It All!
Revamping the Outsourcing Industry
Häftad, Engelska, 2026
627 kr
Skickas inom 5-8 vardagar
This book is a revised version of the PhD dissertation written by the author at the University of Seville, Spain. It proposes a task mining framework that enriches user interface (UI) logs by incorporating visual information through screenshots and eye-tracking data. This approach enables task mining in restrictive industrial environments, such as the secured or virtualized connections common in outsourcing, overcoming the technical limitations of traditional loggers. Beyond merely identifying activities, the framework enables the extraction of underlying decision models to accurately capture the 'as-is' execution of tasks. Consequently, it allows for the construction of decision trees that explain user choices in greater depth, significantly accelerating the analysis of processes targeted for automation. The proposed framework has been validated through a case study involving synthetic mockups and real-life screenshots, demonstrating both a high level of accuracy in capturing user decisions and its practical usefulness in real-world automation initiatives.
E-bok
PDF, Engelska, 2026815 kr
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This book is a revised version of the PhD dissertation written by the author at the University of Seville, Spain. It proposes a task mining framework that enriches user interface (UI) logs by incorporating visual information through screenshots and eye-tracking data. This approach enables task mining in restrictive industrial environments, such as the secured or virtualized connections common in outsourcing, overcoming the technical limitations of traditional loggers. Beyond merely identifying activities, the framework enables the extraction of underlying decision models to accurately capture the 'as-is' execution of tasks. Consequently, it allows for the construction of decision trees that explain user choices in greater depth, significantly accelerating the analysis of processes targeted for automation. The proposed framework has been validated through a case study involving synthetic mockups and real-life screenshots, demonstrating both a high level of accuracy in capturing user decisions and its practical usefulness in real-world automation initiatives.