Data selection focuses on reducing the training time and, at the same time, taking advantage to do better predictions. Too much information is not handy at all since uninformative samples or features may be learnt and consequently the ability to generalize could be hindered. Addressing any problem may mean not having prior knowledge and even to become able, through data selection and even transformation measure, to learn the important data for the forthcoming prediction on unseen data. Depending on the followed methodology to conduct the process model for data mining, the data selection may be named with different names although the core is the same. Tools based on graphical user interfaces are of particular interest in the sense that may make easier the procedure to refine the raw data and eventually to get the ready data to face the mining phase. Data pre-processing deals with many tasks such as data cleansing, attribute selection, instance selection, noise reduction and detecting wrong or distorted labels. Visual data analytics is on the rise especially in multi- dimensional business applications. We encourage to submit very recent applications and if possible unprecedented. Additionally, new theoretical or empirical approaches are welcome.
Topics of interest include, but are not limited to:
The session aims at addressing such issues from practical and theoretical perspectives.
The submitted papers should present results of the original and unpublished research. The papers will be reviewed by the International Program Committee. The best submissions will be selected for presentation and will be included in the conference proceedings.
The conference proceedings will be published by Springer as book chapters in a volume of the KES Smart Innovation Systems and Technologies series, submitted for indexing in Scopus and Thomson-Reuters Conference Proceedings Citation Index (CPCI) and the Web of Science.
Submitted papers should be prepared in Springer style and should be limited to 10 pages. All papers must be submitted electronically via conference submission system.
Antonio J. Tallón-Ballesteros, University of Seville, Spain -
atallon@us.es
Ireneusz Czarnowski, Gdynia Maritime University, Poland - irek@am.gdynia.pl