PACIS 2014 - Business Intelligence and Big Data Analytics Track, Chengdu, China, June 24-28, 2014
Chengdu, China, December 9, 2013 -- PACIS 2014 (http://pacis2014.org/) will be held in Chendu, China, June 24-28, 2014. The Business Intelligence and Big Data Analytics Track is inviting papers on related topics. Business intelligence (BI) technologies have gained increasing attention in recent years, which provide historical, current, and predictive views of business operations based on advanced data collection, extraction, and analysis of large data sets to improve business decision making. In recent decade, Web 2.0 has created an abundance of user-generated contents from online social media such as forums, online groups, web blogs, social networking sites, social multimedia sites, and even virtual worlds. It has begun to usher in a new and exciting era of Business Intelligence research.
More recently "Big Data" and "Big Data Analytics" have been used to describe the data sets and analytical techniques in applications that are so large (from terabytes to exabytes) and complex (from sensor to social media data) that they require advanced and unique data storage, management, analysis, and visualization technologies. Advanced information extraction, topic identification, opinion mining, and time-series analysis techniques can be applied to traditional business information and new BI contents for various accounting, finance, and marketing applications, such as enterprise risk assessment and management, credit rating and analysis, corporate event analysis, stock and portfolio performance prediction, viral marketing analysis, etc.
By designing and evaluating IT artifacts within the organizational and managerial context, much can be learned about BI technologies, practices, and challenges. In this track, we are interested in innovative technologies, methodologies, and theories in business intelligence and big data analytics, which are not limited to a design science approach, but include rigorous and relevant research using management science (analytical modeling and simulation).
Topics of interest include but not limited to:
* E-Commerce and Market Intelligence * Recommender systems * Social media analytics * Opinion mining and sentiment analysis * Crowd-sourcing systems * Social and virtual games * Web mining and analytics for Web 2.0 * Big data analytics in business applications Smart Enterprise Systems * Innovative data warehousing, ETL, and OLAP in BI * Visual interface and HCI for BI * Data and text mining for emerging BI applications * Business process mining and intelligence E-Government and Politics 2.0 * Ubiquitous government services * Equal access and public services * Citizen engagement and participation * Political campaign and e-polling Smart Health and Wellbeing * Human and plant genomics * Healthcare decision support * Patient community analysis Security and Public Safety * Crime analysis * Computational criminology * Terrorism informatics * Open-source intelligence * Cyber security Financial Services Analytics and Intelligence * Intelligent financial process risk monitoring and management * Agent-based modeling and analysis for financial applications * Business intelligence applications for finance * Financial network modeling and analysis * Data-mining for financial applications * Knowledge management for financial organizations Paper Submission Deadline: February 15, 2014 Doctoral Consortium: June 24-25, 2014 Conference: June 24-28, 2014
Roger H.L. Chiang, University of Cincinnati, USA, firstname.lastname@example.org
Shu Schiller, Wright State University, USA, email@example.com
Zhe (Jay) Shan, University of Cincinnati, USA, firstname.lastname@example.org
Harry Jiannan Wang, University of Delaware, USA, email@example.com
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