The Organizers and Program Committee invites submissions of original theoretical research, applied research and deployed application papers on all aspects of Case-Based Reasoning (CBR). ICCBR is the premier, annual meeting of the CBR community and the leading international conference on this topic. The CBR community welcomes experts from related fields and from industry. In particular this year, we seek research related to the intersection of CBR and analogical reasoning, and we have established a special track of the main conference for this purpose. The conference theme for 2018 is: The Future of CBR.
Conference Website: http://iccbr18.com
Deadlines:
Title and Abstract Submission: April 23, 2018
Paper Submission: April 27, 2018
Notification: May 21, 2018
Camera Ready Copy: June 15, 2018
Conference Dates: July 10-12, 2018
The areas of interest covered by ICCBR 2018 include, but are not limited to the following.
Foundations of Case-Based Reasoning
- Similarity measures, case retrieval and indexing
- Case reuse, adaptation and combination
- Maintenance, post-mortem analysis and quality assessment
- Case elicitation, case authoring, knowledge modeling and visualization
- Uncertainty, simulation and prediction
- Context models, explanations, preferences
- Knowledge and experience management
CBR Systems for Task Categories such as
- Process-oriented CBR, workflow management
- Case-based planning, case-based design
- CBR for traces, time-series, and temporal CBR
- Textual CBR
- Social CBR
Computational Analogy (Special Track)
- General analogical reasoning techniques
- Analogical retrieval
- Analogical generalization
- Applications of Computational Analogy
- Frontiers in Computational Analogy
Reasoning with Cases and Related Fields
- Cognitive models and creative reasoning
- Agent-oriented CBR, robotics
- CBR as a cognitive model
- Goal reasoning
- Explainable AI (XAI)
- Cloud-based CBR
- Web-based CBR, recommender systems
- Natural language processing, information retrieval
- Data mining, machine learning and big data
- CBR systems, applications and lessons learned in specific domains.