Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):
C. Dorn, C. Marin, N. Mehandjiev, S. Dustdar:
"Self-learning Predictor Aggregation for the Evolution of People-Driven Ad-Hoc Processes";
Vortrag: Business Process Management 9th International Conference (BPM 2011),
Clermont-Ferrand, France;
30.08.2011
- 02.09.2011; in: "Business Process Management Proceedings of the 9th International Conference (BPM 2011)",
S. Rinderle-Ma, F. Toumani, K. Wolf (Hrg.);
Springer,
LNCS 6896
(2011),
ISBN: 978-3-642-23058-5;
S. 215
- 230.
Kurzfassung englisch:
Contemporary organisational processes evolve with people´s
skills and changing business environments. For instance, process documents
vary with respect to their structure and occurrence in the process.
Supporting users in such settings requires sophisticated learning mechanisms
using a range of inputs overlooked by current dynamic process
systems. We argue that analysing a document´s semantics is of uttermost
importance to identify the most appropriate activity which should
be carried out next. For a system to reliably recommend the next steps
suitable for its user, it should consider both the process structure and the
involved documents´ semantics. Here we propose a self-learning mechanism
which dynamically aggregates a process-based document prediction
with a semantic analysis of documents. We present a set of experiments
testing the prediction accuracy of the approaches individually then compare
them with the aggregated mechanism showing a better accuracy.
Schlagworte:
document analysis, process recommendation, people-driven ad-hoc processes, document and process evolution.
Zugeordnete Projekte:
Projektleitung Schahram Dustdar:
Commius
Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.