RuleML+RR 2024
the 8th International Joint Conference on Rules and Reasoning
Bucharest, Romania
16 - 18 September 2024
Industry track
General Information
The RuleML+RR industry track welcomes original work from all areas of Rules and Reasoning based technologies specifically for solving real industry problems. We are interested in experiences from practitioners when applying rules to industries such as engineering, manufacturing, agriculture, energy, media, financials, telecommunications, healthcare, life sciences, government, smart cities, tourism and cultural heritage.
We encourage submissions on the following topics:
Advanced Uses of Rules and Reasoning in Data Management: Innovations in data access, interpretation, transformation, curation, integration, validation, versioning, and distribution, with a particular focus on scalability and efficiency in industry applications.
Rules and Reasoning for Knowledge Graphs and Ontologies: Cutting-edge methods and tools for building, extending, and maintaining industrial knowledge graphs and ontologies, highlighting their role in enhancing data interoperability and semantic analytics.
Conversational AI with Rules and Reasoning: Breakthroughs in automating communication with customers, suppliers, and service providers, including advanced applications of LLMs, rules and reasoning for understanding, processing data for conversational answers and generating human-like text.
Integration of Rules, Reasoning, and AI Technologies: Novel approaches in combining rules and reasoning with AI technologies, such as LLMs, neuro-symbolic AI, and machine learning, for creating sophisticated industry business applications. In particular exploration of LLM applications for generating insights, automating decision-making processes, and enhancing rule-based systems with deep learning capabilities.
Ethical and Responsible Use of AI and Rules Technologies: Discussions on the ethical considerations, fairness, transparency, and accountability in deploying rules and reasoning technologies, including guidelines and best practices for responsible AI.
Incentives for industry participation in this track include: Present own results / solutions for use of rule technologies in business settings; learn about new trends in rule technologies, and how they can be used to address business problems; exchange experiences about business cases and use of rules.
Submission and Publication
We welcome submissions with original content and will not accept already published papers, advertisements or sales pitches. We recommend the inclusion of information related to: the business case, the technological challenges, the rule-based solution, the status of the approach and the importance of the solution for business.
We welcome extended abstracts limited to 4 pages (including the references) to be submitted to the Industry Track.
Accepted papers will be published as part of CEUR proceedings and should be written in English following in the CEUR-WS.org style template CEURART (1-column variant), available at:
http://ceur-ws.org/Vol-XXX/CEURART.zip
and
https://www.overleaf.com/read/gwhxnqcghhdt.
Reviews will be done by a committee of members from both industry and academia. Submitted papers must be original contributions written in English. Please submit your paper via:
https://easychair.org/conferences/?conf=rulemlrr2024
to the Industry Track.
Important Dates
July 21st, July 31st (extended), 2024: Paper submission deadline
August 4th, August 12th (extended), 2024: Notification of acceptance
September 16th-18th (exact date TBA): Industry Track
For each of these deadlines, a cut-off point of 23:59 AOE applies.
Organization
Chairs
Ioan Toma, Onlim, Austria
Josiane Xavier Parreira, Siemens, Austria
Program Committee
Erwin Filtz, Siemens AG, Austria
Gong Cheng, Nanjing University, China
Juliana Küster Filipe Bowles, University of St Andrews, United Kingdom
Jürgen Umbrich, Onlim, Austria
Mario Scrocca, Cefriel, Italy
Martin Giese, University of Oslo, Norway
Mihai Hulea, Technical University of Cluj-Napoca, Romania
Nikolay Nikolov, SINTEF, Norway
Paul Krause, University of Surrey, United Kingdom
Robert David, Semantic Web Company, Austria
Roman Bauer, University of Surrey, United Kingdom
Simon Steyskal, Siemens AG, Austria
Umutcan Serles, University of Innsbruck, Austria
Thanks to our sponsors
Proceedings
TBA
Keynote
Qi Gao, Senior Data Scientist at Philips Innovation & Strategy
Title: Big data and AI for service innovation of medical imaging systems
Bio: Qi Gao is a senior data scientist and project lead in the Data Science department at Philips Innovation & Strategy. Since 2013, he has been involved in several internal research projects and initiatives on data analytics, machine learning, and NLP in healthcare and personal health. Currently, he focuses on applying (Gen)AI for service innovation of medical devices. He received his PhD from the Delft University of Technology, the Netherlands, for his research on user modeling and recommender systems. He received the Best Paper award at the International Conference on user modeling, adaptation and Personalization 2011 (UMAP2011) and the James Chen Best Student Paper Award in UMAP2012.
Abstract: Medical imaging systems such as MRI, CT, and X-ray are complex devices. They need software upgrades, calibration, and maintenance. To provide optimal clinal performance and predictable system operations, such service activities should be scheduled, predictable, and non-intrusive to minimize the downtime system. In the past years, Philips has invested in Big Data and AI applied to help service engineers prevent system issues and solve customer problems towards the goal of zero-unplanned downtime. In this talk, I will present the achievements with a few relevant use cases and discuss the challenges, particularly, given the rapid development of GenAI.
