The Second Workshop on Synergies between
CBR and Knowledge Discovery
will be held at the
International Conference on Case-Based Reasoning (ICCBR-16)
in Atlanta, Georgia on October 31st, 2016

Call for Papers

At the core of CBR lies the ability of a system to learn from past cases. However, CBR systems often incorporate knowledge discovery methods, for example, to organize their memory or to learn adaptation rules. In turn, knowledge discovery systems often utilize CBR as a learning methodology, for example, through a common set of problems with the nearest-neighbor method and reinforcement learning.  Meanwhile, the machine learning community, which is tightly coupled with knowledge discovery, has historically included CBR among the types of instance-based learning.

This workshop will be dedicated to studying in-depth the possible synergies between case-based reasoning (CBR) and knowledge discovery. It also aims at identifying potentially fruitful ideas for co-operative problem-solving where both CBR and knowledge discovery researchers can compare and combine methods. In particular, new advances in knowledge discovery may help CBR to advance its field of study and play a vital role in the future of knowledge discovery. This second Workshop on Synergies between CBR and Knowledge discovery aims to:

• provide a forum for identifying important contributions and opportunities for research on combining CBR and knowledge discovery,
• promote the systematic study of how to synergistically integrate CBR and knowledge discovery,
• showcase synergistic systems using CBR and knowledge discovery.

Some of the technical issues addressed, and potential outcomes of the workshop, are to identify the knowledge discovery methods used in CBR, to categorize the problems addressed by knowledge discovery in CBR, to propose methodological improvements to fit this context’s needs, preferred types and methods, and guidelines to better develop CBR systems taking advantage of all knowledge discovery research has to offer. Similarly, the workshop will identify the CBR methods used in knowledge discovery, categorize the problems addressed by CBR in knowledge discovery, propose methodological improvements to fit this context’s needs, preferred types and methods, and guidelines to better develop knowledge discovery systems taking advantage of all CBR research has to offer.

We welcome all those interested in the problems and promise of synergistically combining CBR and knowledge discovery whether they belong to the CBR community, the knowledge discovery community, or the machine learning community.

Topics of interest include (but are not limited to):

• Architectures for synergistic systems between CBR and knowledge discovery
• Theoretical frameworks for synergistic systems between CBR and knowledge discovery
• Memory structure mining in CBR
• Memory organization mining in CBR (decision tree induction, etc.)
• Case mining
• Feature selection in CBR
• Knowledge discovery in CBR (adaptation knowledge, meta-knowledge, etc.)
• Concept mining in CBR
• Image and multimedia mining in CBR
• Temporal mining in CBR
• Text mining in CBR
• Signal mining in CBR
• Web mining and CBR
• Nearest-neighbor systems and CBR
• Instance-based learning and CBR
• Reinforcement learning and CBR
• CBR and statistics
• CBR and statistical data analysis
• CBR in multi-strategy learning systems
• CBR and similarity and metric learning
• CBR and Big Data
• CBR and deep learning
• Application specific synergies between CBR and knowledge discovery (medicine, bioinformatics, social networks, sentiment analysis, etc.).

Paper presentations will be interspersed with discussions in which we characterize, categorize, and discuss the synergies between CBR and knowledge discovery. A wrap-up round table discussion will summarize the lessons learnt, issues identified, and future directions.

Submission Requirements

Submitted papers are limited to 10 pages in length. All papers are to be submitted via the CBRKD 2016 EasyChair system. Papers should be in Springer LNCS format. Author's instructions, along with LaTeX and Word macro files, are available at http://www.springer.de/comp/lncs/authors.html.

Submissions should be original papers that have not already been published elsewhere. However, papers may include previously published results that support a new theme, as long as all past publications are fully referenced.

Dates

• Submission Deadline: August 1st 23, 2016
• Notification Date: September 5, 2016
• Camera-Ready Deadline: September 25, 2016
• Workshop Date: October 31, 2016

Workshop Web Site

http://cs.oswego.edu/~bichinda/iccbr2016/

Submission Web Site

https://easychair.org/conferences/?conf=cbrkd2016

Organizing Committee

Co-Chairs

Isabelle Bichindaritz
State University of New York at Oswego, USA
ibichind@oswego.edu.

Cindy Marling
Ohio University, USA 
marling@ohio.edu 

Stefania Montani
University of Piemonte Orientale, Italy
stefania.montani@unipmn.it.
 

Committee Members

Agnar Aamodt, NTNU, Norway

Klaus-Dieter Althoff, DFKI and University of Hildesheim, Germany

Juan Manuel Cortado, University of Salamanca, Spain

Beatriz Lopez, University of Girona, Spain

Jean Lieber, Loria, University of Nancy, France

Luigi Portinale, University of Piemonte Orientale, Italy

Rainer Schmitt, University of Rostock, Germany

Olga Vorobieva, I. M. Sechenov Institute of Evolutionary Physiology and Biochemistry, Russia

We look forward to welcoming you to Atlanta !