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  4. Learning process modeling phases from modeling interactions and eye tracking data
 
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Learning process modeling phases from modeling interactions and eye tracking data

Journal
Data & Knowledge Engineering
Type
journal article
Date Issued
2019
Author(s)
Burattin, Andrea
Kaiser, Michael
Neurauter, Manuel
Weber, Barbara  
DOI
https://doi.org/10.1016/j.datak.2019.04.001
Abstract (De)
The creation of a process model is a process consisting of five distinct phases, i.e., problem understanding, method finding, modeling, reconciliation, and validation. To enable a fine-grained analysis of process model creation based on phases or the development of phase-specific modeling support, an automatic approach to detect phases is needed. While approaches exist to automatically detect modeling and reconciliation phases based on user interactions, the detection of phases without user interactions (i.e., problem understanding, method finding, and validation) is still a problem. Exploiting a combination of user interactions and eye tracking data, this paper presents a two-step approach that is able to automatically detect the sequence of phases a modeler is engaged in during model creation. The evaluation of our approach shows promising results both in terms of quality as well as computation time demonstrating its feasibility."
Language
English
Keywords
Process of process modeling
Eye tracking
Interaction tracking
Automatic phase detection
Classification
Sequence labeling
HSG Classification
contribution to scientific community
Refereed
Yes
Official URL
http://www.sciencedirect.com/science/article/pii/S0169023X17303282
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/99125
Subject(s)

computer science

Division(s)

ICS - Institute of Co...

SCS - School of Compu...

Eprints ID
257006
File(s)
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Thumbnail Image

open.access

Name

1-s2.0-S0169023X17303282-main.pdf

Size

2.1 MB

Format

Adobe PDF

Checksum (MD5)

a392c5c3bebf24ff72bd6dd90b2263d9

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