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== CALL FOR PAPERS ==
WORKSHOP ON ARTIFICIAL INTELLIGENCE FOR BUSINESS PROCESS
MANAGEMENT
http://ai4bpm.inf.unibz.it
in conjunction with the 17th Business Process Management
Conference (BPM
2019)
September 1 - 6, 2019, Vienna, Austria
The field of Artificial Intelligence continues to grow, with new
and deeper
techniques, and with application across numerous areas. In the
past few
years we have seen strong interest from both industry and academia
in
applying AI techniques in the area of Business Process Management.
Indeed,
the application of AI is impacting additional areas where process
management perspectives and techniques are relevant, including
industrial
engineering, IoT, and emergency response, to name a few. The use
of AI in
BPM has been discussed as the next disruptive technology that will
touch
almost all of the business process activities being performed by
humans.
In some cases AI will dramatically simplify human interaction with
a
process, in other cases it will extensively support humans in the
execution
of tasks, and in yet other cases it will enable full automation of
tasks
that have traditionally required manual contributions. Over time
AI may
lead to entirely new paradigms for business processes and
operations. For
example, instead of BPM models centered on process or on case
management,
we anticipate models that are based fundamentally on goal
achievement, as
well as we anticipate models that fully enable continuous
improvement and
adaptation based on experiential learning.
The workshop encourages papers describing original research and
industrial
experiences that explore how AI can be applied in BPM contexts.
AI4BPM 2019 welcomes submissions that make use of techniques
coming from
all areas of AI, including (but not limited to) machine learning,
search,
planning, knowledge representation, information extraction,
reasoning,
constraint satisfaction, natural language processing, robotics and
perception, and multi-agent systems.
== TOPICS OF INTEREST ==
The workshop emphasizes the use of AI in across the spectrum of
application
areas where process management perspectives and techniques are
relevant. In
addition to traditional BPM contexts this includes industrial
engineering,
IoT applications, emergency response, autonomous systems, emerging
financial models, infrastructure and technical support services,
and
others. The workshop topics may include (but are not limited to)
the
following:
- Techniques for discovering and automating tasks, processes and
rules from
unstructured data
- Process Mining augmented with Natural Language Understanding
against
unstructured data
- Knowledge representation and reasoning about process
specifications and
instances
- Goal-driven approaches to process management
- Virtual assistants to simplify interaction with processes
- AI-enabled creation of virtual assistant dialogues, including
automated
interaction with back-end systems
- Machine Learning to support automated triage and work assignment
- Machine Learning to enable automated trouble ticket resolution
- AI-enabled automation of exception handling
- Application of AI to (Data-Driven) BPM
- AI-enriched robotic process automation
- AI-enabled creation of robotic process automation solutions
- AI-driven modelling and optimization of business processes
- AI enablement for Knowledge-intensive Processes
- AI-based enrichment of IoT-enabled processes
- Applications of AI for Blockchain-hosted processes
- Applications of AI in managing industrial and manufacturing
processes
- Applications of AI in industry-specific business processes
(retail,
e-commerce, finance, manufacturing, healthcare)
- Datasets and baselines for AI applied to BPM
- AI-enabled approaches for enhancing or transforming the BPM
lifecycle
- Impact of AI technology on BPM-related standards such as BPMN,
CMMN and
DMN
- Non-traditional models and approaches to process management that
leverage
AI
- Social, economic, and business impacts of infusing AI into
process
management
Given that the research area of AI for BPM is in its infancy, we
especially
encourage submissions that explore totally new directions, which
step
outside of the areas listed above.
== SUBMISSIONS ==
Accepted submissions:
- Research papers, up to 12 pages, describing original and novel
research
work, including research results and evaluations. Research papers
should
not have been published or submitted for publication concurrently
elsewhere.
- Experience papers, up to 12 pages, describing experiences with
the novel
application of AI techniques to BPM. Such papers should include
clear
descriptions of the motivations underlying the use of AI for BPM,
the value
obtained through the use of AI, and the challenges that needed to
be
overcome. Experience papers should not have been published or
submitted
for publication concurrently elsewhere.
- Challenge Statements, at least 4 and up to 6 pages, presenting a
position
on issues related to the topics of the workshop. These statements
would
lead to interesting discussion by raising key questions,
controversial
point of views, challenges, and ideas to address the identified
issues.
The discussion session(s) will be based on one or more of the
Challenge
Statements received.
Papers should be written in English, following the
Springer_LNCS_format.
All submissions will be reviewed by the workshop organizers and
selected PC
members. The submission process will be managed using the
Easychair
conference management system. Depending on the quality of
submissions, we
also consider publishing long versions of papers and challenge
statements
in a special issue of the Journal on Data Semantics or a similar
forum.
== IMPORTANT DATES ==
- Submission deadline: 24 May, 2019
- Notification deadline: 28 June, 2019
- Camera-ready deadline: 12 July, 2019
- Workshop: 2 September, 2019
== ORGANIZERS ==
Fabrizio Maria Maggi, University of Tartu, Estonia
Andrea Marrella, Sapienza University of Rome, Italy
Arik Senderovich, University of Toronto, Canada
Emilio Sulis, University of Turin, Italy
== PROGRAM COMMITTEE ==
- Han van der Aa, Humboldt University of Berlin, Germany
- Matteo Baldoni, Dipartimento di Informatica, University of
Turin, Italy
- Emna Hachicha Belghith, University of Caen Normandy
- Ralph Bergmann, University of Trier, Germany
- Andrea Burattin, DTU, Copenhagen, Denmark
- Federico Chesani, University of Bologna, Italy
- Claudio Di Ciccio, Vienna University of Economics and Business,
Austria
- Schahram Dustdar, TU Wien, Austria
- Peter Fettke, German Research Center for Artificial
Intelligence,
Germany
- Avigdor Gal, Technion, Israel
- Krzysztof Kluza, AGH University of Science and Technology
- Henrik Leopold, VU University Amsterdam, the Netherlands
- Massimo Mecella, Sapienza University of Rome, Italy
- Paola Mello, University of Bologna, Italy
- Roberto Micalizio, University of Turin, Italy
- Fabio Patrizi, Sapienza University of Rome, Italy
- Giulio Petrucci, Google, Switzerland
- Manfred Reichert, University of Ulm, Germany
- Niek Tax, Booking.com, Amsterdam, the Netherlands
- Irene Teinemaa, Booking.com, Amsterdam, the Netherlands
- Daniele Theseider Dupre', University of Eastern Piedmont, Italy
- Hagen Voelzer, IBM Zurich Research Lab, Switzerland
- Matthias Weidlich, Humboldt University of Berlin, Germany
== MORE INFORMATION ==
Visit the workshop website
http://ai4bpm.inf.unibz.it/ for
detailed
submission information.
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