Call for Papers
Scope
Knowledge discovery in databases (KDD) has become a process of considerable interest in recent years as the amounts of data in many databases have grown tremendously large. This process generally consists of the following three phases: Pre-processing, Data Mining (DM) and Post-processing. DM plays a critical role to the KDD process. It involves applying specific algorithms for automatically discovering high level knowledge from real world, large and complex data sets. This idea of automatically discovering knowledge from databases is a very attractive and challenging task, both for academia and industry. Hence, there has been a growing interest in DM in several Artificial Intelligence (AI)-related areas.
Soft Computing (SC) is an AI area comprising of a consortium of methodologies that works synergistically and provides, in one form or another, flexible information processing capability for handling real-life ambiguous situations. Its aim is to exploit the tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve tractability, robustness and low-cost solutions. The guiding principle is to devise methods of computation that lead to an acceptable solution at low cost by seeking for an approximate solution to an imprecisely/precisely formulated problem.
All these have prompted that SC methodologies are most widely applied in DM. So, this topic has presented considerable interest in the Computation Intelligence community in the last few years.
The aim of the session is to provide a forum to disseminate and discuss Soft Computing approaches in classification, regression and unsupervised learning (association rules, clustering, etc), with special attention to the Evolutionary Knowledge Extraction and Data Mining. We want to offer an opportunity for researchers and practitioners to identify new promising research directions in this area.
Topics
Topics include, but are not restricted to:
- Evolutionary Knowledge Extraction
- Fuzzy Data Mining
- Scalability: large scale data mining, distributed model, etc
- Interpretability
- Data Preprocessing and Soft Computing
- Software for Data Mining and Evolutionary Knowledge Extraction
- etc.
Paper Submission
Please follow the instructions given at the corresponding section.
Organizers
- Jesús Alcalá-Fdez: jalcala@decsai.ugr.es
Department of Computer Science and Artificial Intelligence, University of Granada, Spain. - Daniel Sánchez: daniel.sanchezf@softcomputing.es
Unit of Cognitive Computing: Computing with Perceptions, European Centre for Soft Computing, Spain.