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Invited Session on
Interdisciplinary Approaches in Business Intelligence Research and Practice (IABIRP 2016)
URL: http://idt-16.kesinternational.org/cmsISdisplay.php

Organized within the framework of the 7th International Conference on Intelligent Decision Technologies (KES IDT 2016)

Puerto de la Cruz, Tenerife, Spain, 15 - 17 June, 2016
URL: http://idt-16.kesinternational.org/

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SCOPE & TOPICS

One of the ever hot issues in many organization systems is how to transform large amounts of daily collected operational data into the useful knowledge from the perspective of declared company goals and expected business values. The main concern of this invited session is a Business intelligence (BI) paradigm, as a set of theories, methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information. Various interdisciplinary oriented BI approaches may provide organizations the ability to use their data to improve quality of business, increase financial efficiency and operational effectiveness, conduct innovative research and satisfy regulatory requirements. Applications of appropriate BI implementation methodologies together with outcomes related to collaborative and interdisciplinary approaches are inevitable when applying BI approaches to large and complex organization systems. For many years, such interdisciplinary approaches were used in analyzing big data gathered from not only business sectors, but also public, non-profit, and government sectors.

The main goal of the session is to attract researchers who will present their contributions, interdisciplinary approaches or case studies in the area of BI. The focusmay be set to various BI aspects, such as: data warehousing, reporting, online analytical processing, analytics, data mining, process mining, text mining, predictive analytics and prescriptive analytics, as well as various aspects of big data analysis and time series analysis. We express a special interest in gathering scientists and practitioners interested in applying BI approaches predominantly in public and government sectors, such as healthcare, education, or security services. However, experts from all other sectors are also welcomed.

Submissions are expected from, but not limited to the following topics:

* Business Intelligence – Theoretical and practical aspects
* BI Applications and Industry Experience
* Data Warehousing, Data Mining, Online Analytical Processing, and Reporting Capabilities
* Predictive analytics and Prescriptive analytics
* Statistical analysis and characterization
* Process Mining, Pattern Mining, and Swarm Intelligence
* Decision and Regression Trees
* Data quality assessment and improvement: preprocessing, cleaning, missing data, etc.
* Semi-structured or unstructured data in BI systems
* Information integration for data and text mining
* Cloud-computing models and scalability in BI systems
* Data privacy and security issues in BI systems
* Business Intelligence and Analytics for Healthcare
* Educational Data Mining
* Social network data analysis
* Web survey methods in business intelligence
* Organizational and human factors, skills, and qualifications for BI Approaches
* Teaching BI approaches in academic and industrial environments


PAPER SUBMISSION


* Papers will be refereed and accepted on the basis of their scientific merit and relevance to the workshop.
* The papers will be scheduled for presentation either orally or by poster, depending on their attributes, author preferences and referee recommendations. Please note that poster presentations are regarded as being of equal importance to oral presentations.
* The required paper length is 10 pages in publisher format. Papers longer than this may be subject to an additional charge. Papers much longer or shorter than the required length may be rejected, at the decision of the organisers.


IMPORTANT DATES

* Paper submission: 18 January, 2016
* Acceptance notification: 15 February, 2016
* Final paper submission: 7 March, 2016
* Conference: June 15 - 17, 2016


WORKSHOP CHAIRS

* Ivan Lukovic, University of Novi Sad, Serbia
(http://www.acs.uns.ac.rs/en/user/10, ivan@uns.ac.rs)