Actividades formativas de doctorado
D442004On the role of textual data in determining business process complexity. Research insights from ITSM case studies
Organiza: Luis Fernández Sanz - Grupo de Investigación TIFyC

Inscripción en:
(en este momento no hay plazo abierto para preinscripción en este curso)

Coordinación: Luis Fernández Sanz
Plazas ofertadas: 30
Duración: 1.5 horas     Tipo: Específico
Modalidad: Mixta (Presencial + virtual)

Lugar de impartición: Escuela Politécnica Superior

Fechas de impartición
15/12/2022 - 12-13:30

Estudiantes del programa y estudiantes de la rama de conocimiento

Descripción general

To support efficient business process execution and business operations, today’s organizations, both private and governmental, increasingly rely on information systems (IS) in their IT landscape. Latest IT Ticket Management systems, in addition to diverse IT service-specific features like Incident, Problem, Release or Change Management, also provide workflow management support, reporting and analysis for informed decision-making, service catalogues, and multiple channel communication support. Such a variety of features and wide coverage allows IS to record vast amounts of data, including event log, i.e., process execution history, and textual data massively generated by process actors and making up more than 80% of data in organizations.

This seminar is devoted to the investigation of the effects of textual data serving as an input to a process on the actual process execution and is based on the Ph.D. research conducted in two IT Service Management (ITSM) case studies – customer request / IT ticket processing.


The following topics will be addressed in the seminar: research motivation and context, limitations of the textual data usage and analysis in Business Process Management, design of linguistic features aimed at business process complexity analysis, predicting business process complexity based on textual data and simple ML, enriching textual data-based process complexity with event log complexity insights, implications for research and practice, future research.


Aleksandra Revina, Ph.D. candidate at the Technical University of Berlin and Brandenburg University of Applied Sciences (BUAS), currently working as an academic and research staff at BUAS on various projects, i.a., digitalization. Her research interests include but are not limited to diverse methods and tools for business process analysis and automation from such subject fields as Business Information Systems, Business Process Management, Text Analytics, and Linguistics. The ultimate goal is to develop efficient decision-making support for process workers.


Sesión única de presentación en modalidad híbrida (presencial y remota) con turno de debates y preguntas al final

Sistema de evaluación

Asistencia presencial o a través de Collaborate (con informe de conexión) y superar la prueba de preguntas sobre la presentación disponible en el correspondiente curso de Aula Virtual