Papers of the Chair of Process Analytics at the BPM Conference
Due to this year's virtual set-up, registration for the conference is currently free and open until September 9.
Our members are involved in the following works:
Privacy-preserving event log sanitization (Main track):
- Stephan A. Fahrenkrog-Petersen, Han van der Aa, Matthias Weidlich:
PRIPEL: Privacy-Preserving Event Log Publishing Including Contextual Information
Stemming from research conducted at the Humbolt-Universität zu Berlin, this paper presents a new state-of-the-art technique for the sanitization of event data recorded during process execution. The primary goal of the technique is to ensure that published event logs do not disclose personal information about actors involved in a process, while maintaining as much utility for process mining techniques as possible.
IoT-Based Activity Recognition (BPM Forum):
- Adrian Rebmann, Jana-Rebecca Rehse, Mira Pinter, Marius Schnaubelt, Kevin Daun, Peter Fettke:
IoT-Based Activity Recognition for Process Assistance in Human-Robot Disaster Response
Stemming from research conducted at the DFKI, this paper demonstrates how activity recognition over IoT data can be employed as a means to provide process assistance in emergency response situations where ground robots accompany human team members.
Transforming natural language statements into declarative process constraints
- Anti Alman, Karl Johannes Balder, Fabrizio M. Maggi, Han van der Aa:
Declo: A Chatbot for User-friendly Specification of Declarative Process Models
(Demo track) - Han van der Aa, Karl Johannes Balder, Fabrizio M. Maggi, Alexander Nolte:
Say It In Your Own Words: Defining Declarative Process Models Using Speech Recognition
(BPM Forum)
These works both stem from thesis projects conducted by students of the University of Tartu, Estonia. Both provide user-friendly support for the establishment of declarative (i.e., constraint-based) process models. This is achieved through the transformation of natural language statements into declarative constraints. The Demo paper supports this use case through a conversational agent (i.e., a chatbot), whereas the BPM Forum paper allows users to describe models in a speech-based manner. Aside from the application of speech2text, the latter paper also provides considerable improvements in terms of coverage and quality over our previous work.
These papers are both part of the RuM software.