IJBIDM provides a forum for state-of-the-art developments and research as well as current innovative activities in business intelligence, data analysis and mining. Intelligent data analysis provides powerful and effective tools for problem solving in a variety of business modelling tasks. IJBIDM highlights 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.
Journal Home: Journal Homepage
Editor-in-Chief: Dr. Mahardhika Pratama
scope: Data extraction/reporting/cleaning/pre-processing OLAP, decision analysis, causal modelling Reasoning under uncertainty, noise in data Business intelligence cycle Model specification/selection/estimation Web technology, mining, agents Fuzzy, neural, evolutionary approaches Genetic algorithms, machine learning, expert/hybrid systems Bayesian inference, bootstrap, randomisation Exploratory/automated data analysis Knowledge-based analysis, statistical pattern recognition
Print ISSN: 1743-8187
Electronic ISSN: 1743-8195
Abstracting and Indexing: Scopus
Imapct Factor :
Subject Area and Category: Business, Management and Accounting,Management Information Systems,Decision Sciences,Information Systems and Management
Publication Frequency:
H Index: 19
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Q4: Statistics, Probability and Uncertainty
Cite Score: 0.8
SNIP: 0.641
Journal Rank(SJR): 0.166
Guidelines for Authors: International Journal of Business Intelligence and Data Mining Author Guidelines
Publisher: Inderscience Enterprises Ltd
Country: United Kingdom