Call for Papers: Learning (Business) Rules from Data
RuleML 2014 Special Track: Learning (Business) Rules from Data
Papers submitted to the track could address (among others) extraction of business rules from sets of fuzzy, uncertain and possibly conflicting rules learned from data and bridging the gap between rules as "correlations" in the data and rules that can be used in business rule management systems.
Topics
- Learning Action, Association, Decision and Constraint Rules from Data
- Extracting business rules from decision trees and rule sets induced from data
- Non-monotonic, uncertain and defeasible reasoning to resolve conflicting rules
- Enhancing rule learning processes with domain knowledge
- Fuzzy and probabilistic extensions to rule markup languages (SBVR, RuleML, PMML)
- Rule interest/quality measures suitable for business rule learning
- Learning disjunctive and negative rules in business rules context
Organisers
Tomáš Kliegr (University of Economics, Prague, Czech Republic) and Davide Sottara (Arizona State University, USA)
Important Dates for RuleML (including the special tracks)
Extended abstract submission: | April 14, 2014 |
Extended paper submission: | April 22, 2014 |
Notification: | May 20, 2014 |
Camera ready: | June 6, 2014 |
RuleML 2014 dates: | August 18-20, 2014 |
Submission guidelines
Papers must be original contributions written in English and must be submitted at EasyChair for the special track as:
- Full Papers (15 pages in the proceedings)
- Short Papers (8 pages in the proceedings)
Please upload all submissions in LNCS format. To ensure high quality, submitted papers will be carefully peer-reviewed by 3 PC members based on originality, significance, technical soundness, and clarity of exposition. Accepted papers will be published in book form in the Springer Lecture Notes in Computer Science (LNCS) series within the RuleML main track proceedings.
Program Committee
Submitted papers will be reviewed by three PC members from the industry and academia.
Industry
Jerome Boyer
(IBM) professional bio...Jerome Boyer is the IBM Expert on Operational Decision Management, BPM, and SOA. As an IBM senior technical staff member, Jerome assumes a leadership role within IBM Software Services for WebSphere (ISSW), as a lead BPMS and BRMS Solution Architect. With more than 20 years of experience in directing, managing and developing large-scale, enterprise-wide IT solutions in the following: Telecom, Insurance, Financial, .com market. Jerome is deeply involved in the business and technical architecture for most IBM ODM engagements. He is also book author of "Agile Business Rule Development Process, Architecture, and JRules Examples", and multiple IBM developer works and BPM Journal articles.
Jacob Feldman
(Open Rules) professional bio...This email address is being protected from spambots. You need JavaScript enabled to view it. is the founder and CTO of OpenRules, Inc., a US corporation that created and maintains the popular Open Source Business Decision Management System commonly known as "OpenRules". He has extensive experience in development of decision support software using Business Rules, Optimization, and Machine Learning technologies for real-world mission-critical applications. He has 5 granted patents in the area of Business Rules and Constraint Programming. Jacob is a frequent presenter at the major decision management events. He is also a specification lead for the JSR-331 standard.
Alex Guazzelli
(Zementis) professional bio...Dr. Alex Guazzelli has helped shape PMML and is currently working with the other DMG members in adding even more features and capabilities to the standard. As the Vice President of Analytics at Zementis, Inc., Dr. Guazzelli is responsible for developing core technology and analytical solutions under ADAPA, a PMML-based predictive decisioning platform. Prior to joining Zementis, Dr. Guazzelli was involved in not only building but also deploying predictive solutions for large financial and telecommunication institutions around the globe. In academia, Dr. Guazzelli worked with data mining, neural networks, expert systems and brain theory. Dr. Guazzelli holds a Ph.D. in Computer Science from the University of Southern California and a M.S and B.S. in Computer Science from the Federal University of Rio Grande do Sul, Brazil.
Petr Máša
(freelance data mining consultant) professional bio...Dr. Petr Masa graduated at the University of Economics, Prague and Charles University. He worked in the area of data analysis, data mining and big data in the following industries: banking, insurance, telecommunications and retail. Recent Petr Masa's engagements include Adastra (senior data mining manager), KPMG and Deloitte. Petr Masa has a track record of more than 100 completed data mining, data analysis and data governance projects.
Mark Proctor
(Drools/Red Hat)Christian De Sainte Marie
(IBM)
Academia
- Martin Atzmueller (University of Kassel, Germany)
- Agnieszka Dardzinska (Bialystok University of Technology, Poland)
- Johannes Fürnkranz (TU Darmstadt, Germany)
- Martin Holeňa (Academy of Sciences, Czech Republic)
- Jiří Ivánek (University of Economics Prague, Czech Republic)
- Evelina Lamma (Università degli Studi di Ferrara, Italy)
- Florian Lemmerich (University of Würzburg, Germany)
- Zbigniew W. Ras (University of North Carolina, Charlotte, USA)
- Fabrizio Riguzzi (Università degli Studi di Ferrara, Italy)
- Milan Šimůnek (University of Economics Prague, Czech Republic)