International Journal of Business Intelligence and Data Mining (IJBIDM)
The International Journal of Business Intelligence and Data Mining (IJBIDM)
publishes and disseminates knowledge on an international basis in the areas
of business intelligence, intelligent data analysis, and data mining. It
provides a forum for state-of-the-art developments and research, as well as
current innovative activities in business intelligence, data analysis and
mining. In contrast to other journals, IJBIDM focuses on the application of
data analysis and mining techniques in business applications.
Intelligent data analysis provides powerful and effective tools for problem
solving in a variety of business modelling tasks. IJBIDM is devoted to
intelligent techniques used for business modelling, including all areas of
data visualisation, data pre-processing (fusion, editing, transformation,
filtering, sampling), data engineering, data mining techniques, tools and
applications, neurocomputing, evolutionary computing, fuzzy techniques,
expert systems, knowledge filtering, and post-processing.
IJBIDM is devoted to the publications of high quality papers on theoretical
developments and practical applications in business intelligence, data
analysis and data mining. Original research papers, state-of-the-art
reviews, and technical notes are invited for publications. Special issues
are devoted to current issues in business intelligence and techniques.
IJBIDM also publishes best papers from international conferences in the
areas relevant to the journal.
Papers published in IJBIDM are geared heavily towards applications (use of
intelligence data analysis and mining techniques in business applications),
with an anticipated split of 70% of the papers published being
applications-oriented, research and the remaining 30% containing more
ISSN (Online): 1743-8195
ISSN (Print): 1743-8187
Dr. David Taniar
School of Business Systems
Clayton, Victoria 3800
Content available by subscription. Free sample content available online.
Abstracts available online. Articles available in PDF format.
Current Issue: Volume 2 Issue 4 2007
Date: 29 January 2008