Business Intelligence and Analytics

Business Intelligence and Analytics

Research Goal

E-Commerce applications present unique challenges and opportunities for developing various data mining, text mining, and web mining techniques for business intelligence and knowledge management purposes. Based on more than one decade of research funded by NSF and major commercial companies (HP, SAP, DEC, AT&T, CommerceOne, etc.), the University of Arizona Artificial Intelligence Lab has conducted E-Commerce Intelligence and Mining research in the following application areas:

  • Business Intelligence: Multilingual e-commerce portals and knowledge mapping systems
  • Group Decision Support Systems (GDSS): Text mining and visualization to support collaboration
  • Credit Rating: Data mining for international credit rating analysis
  • ERP Knowledge Management: Knowledge mapping research for ERP content mining
  • Patent Analysis: Text and citation based analysis of international patents
  • E-Commerce Recommender Systems: Graph-based models for customer relation management (CRM) and product recommendation
  • E-Commerce Security Analysis: Text and web mining for detecting fraudulent web sites and e-commerce contents
  • Stock Prediction Systems: Text mining based stock outbreak detection
  • E-Commerce Marketing and Survey: Opinion mining for Web 2.0 customer-generated contents and sentiment analysis
  • Finance and Accounting Text Mining: Earnings, return, volatility, and volume prediction based on mass media (press) and social media

For more information see: H. Chen, "Business and Market Intelligence 2.0," Special Issue of IEEE Intelligent Systems, Trends & Controversies. January-February 2010.

Approach and Methodology

Business Intelligence (BI), a term coined in 1989, has gained much traction in the IT practitioner community and academia over the past two decades. According to Wikipedia, BI refers to the “skills, technologies, applications, and practices used to help a business acquire a better understanding of its commercial context.” Based on a survey of 1,400 CEOs, the Gartner Group projected BI revenue to reach $3 billion in 2009. According to an IBM Global CIO Study, the collective voice of more than 2,500 Chief Information Officers worldwide points to business intelligence and analytics as the top visionary plan for enhancing their enterprises’ competitiveness. As a data-centric approach, BI heavily relies on advanced data collection, extraction, and analysis technologies, including: data warehousing, Extraction, Transformation, and Load (ETL), Business Performance Management (BPM), and advanced knowledge discovery using data and text mining. In the past five years, web intelligence, web analytics, web 2.0, and user-generated contents have also begun to usher in a new and exciting era of Business Intelligence 2.0 (BI 2.0) research. Given these tremendous developments, Design Science based information systems research can contribute significantly to BI. By designing and evaluating IT artifacts within the organizational and managerial context, much can be learned about BI technologies, practices, and challenges.

Funding (Selected)

We thank the following agencies and companies for providing research funding support:

  • NSF (SGER). "Inter-Repository Patent Analysis to Understand Worldwide Nanotechnology Research and Development, " December 2007 – December 2008 ($100,000).
  • NSF (SGER). "Worldwide Nanotechnology Development: A Comparative Study of Global Patents," January 2007-December 2007 ($100,000).
  • NSF (DMI-0533749). "NanoMap: Mapping Nanotechnology Development," August 2005-July 2007 ($200,000).
  • NSF (SGER). "Mapping Nanotechnology Development based on the ISI Literature-Citation Database." September 2005-August 2006 ($100,000).
  • NSF, National Science Digital Library (NSDL) Program. "An Active Object-Oriented Digital Library for Microeconomics Education," September 2002-August 2004 ($700,000).
  • Mark and Susan Hoffman E-Commerce Lab ($1M naming endowment); $500,000 equipment donation from HP;, ERP and e-commerce software donations from Oracle, SAP, J.D. Edward, IBM, Microsoft, and IFS (combined value of $10M), October 2000.
  • Digital Equipment Corporation, External Technology Grants program. DEC AlphaServer 4100 (5/533 Mhz CPU, 2 GBs RAM, 100 GBs disk). 1997 - 2001 ($184,893; equipment donation); and "E-Commerce Agent Research and Curriculum Development through HP E-speak: A Framework for Creating Wireless B2B Solutions," June 2000 - May 2001 ($122,729).
  • Hewlett-Packard Company University Grant. "Hewlett-Packard Enterprise Computing Lab for Enterprise Information Systems Education and Research," July 1999 ($305,578).
  • Silicon Graphics, Inc. (SGI). SGI Origin2000 supercomputer (8 R10000 processors, 1 GB RAM, 100 GBs disk), 1998 - 2001 ($210,000; equipment donation).
  • 3COM, "High-Performance Multimedia System Benchmarking: An Experiment for Internet-2, "October 1998 - February 1999 ($90,000).
  • SAP University Alliance Grant Awards. "Knowledge Management for SAP R/3: An Experiment on Call Center Record Management," January 1999 - December 1999 ($75,000).
  • AT&T Foundation Special Purpose Grants in Science and Engineering. "Intelligent Internet Resource Categorization and Discovery," October 1996 - September 1996 ($10,000).



  • H. Chen and M. Roco, "Mapping Nanotechnology Innovations and Knowledge: Global and Longitudinal Patent and Literature Analysis," Springer, 2008.
  • H. Chen, Trailblazing a Path Towards Knowledge and Transformation: E-Library, E-Government, and E-Commerce, The University of Arizona, Tucson, Arizona, January, 2003.
  • H. Chen, Knowledge Management Systems: A Text Mining Perspective, University of Arizona, Tucson, Arizona, November, 2001.




  • Q. Li, Y. Chen, L. L. Jiang, P. Li, and H. Chen, “A Tensor-based Information Framework for Predicting the Stock Market,” ACM Transactions on Information Systems, forthcoming, 2016.


  • J. Woo, M. J. Lee, Y. Ku, and H. Chen, “The Impact of Individual Attributes on Knowledge Diffusion in Web Forums,” Quality and Quantity, Volume 49, Number 6, Pages 2221-2236, 2015.
  • A. Abbasi, F. Zahedi, D. Zeng, Y. Chen, H. Chen, and J. F. Nunamaker, “Enhancing Predictive Analytics for Anti-Phishing by Exploiting Website Genre Information,” Journal of Management Information Systems, Volume 31, Number 4, Pages 109-157, 2015.
  • D. Zimbra, H. Chen, and R. F. Lusch, “Stakeholder Analyses of Firm-Related Web Forums: Applications in Stock Return Prediction,” ACM Transactions on Management Information Systems, Volume 6, Number 1, Pages 2:1-2:38, 2015.
  • S. Jiang, D. Zimbra, J. F. Nunamaker, and H. Chen, “Analyzing Firm-specific Social Media and Market: A Stakeholder-based Event Analysis Framework,” Decision Support Systems,” Volume 67, Pages 1-130 (November 2014).
  • C. Jiang, K. Liang, H. Chen, Y. Ding, "Analyzing Market Performance via Social Media: A Case Study of a Banking industry Crisis," SCIENCE CHINA Information Sciences, Volume 57, Number 5, Pages 1-18, 2014
  • J. L. Campbell, H. Chen, D. S. Dhaliwal, H. Lu, and L. B. Steele, "The Information Content of Mandatory Risk Factor Disclosures in Corporate Filings," Review of Accounting Studies, Volume 19, Number 1, Pages 396-455, October, 2013
  • E. Lim, H. Chen, and Q. Chen, "Business Intelligence and Analytics: Research Directions," ACM Transactions on Management Information Systems, Volume 3, Number 4, Pages 17: 1-17: 10, January, 2013.
  • L. Fan, Y. Zhang, Y. Dang, and H. Chen, "Analyzing Sentiments in Web 2.0 Social Media Data in Chinese: Experiments on Business and Marketing Related Chinese Web Forums," Information Technology and management,  Volume 14, Number 3, Pages 231-242, 2013.
  • H. Chen, Roger Chiang, and Veda Storey, "Business Intelligence and Analytics: From Big Data to Big Impact," MIS Quarterly, Volume 36, Number 4, Pages 1165-1188, December 2012
  • H.M. Lu, T. T. Tsai, H. Chen, M. W. Hung, and S. H. Li, "Credit Rating Change Modeling using News and Financial Ratios," ACM Transactions on Management Information Systems, Volume 3, Number 1, Pages 14:1-14:30, 2012
  • X. Li and H. Chen, “Recommendation as Link Prediction in Bipartite Graphs: A Graph Kernel-based Machine Learning Approach,” Decision Support Systems, 2012.
  • R.P. Schumaker, Y. Zhang, C. Huang, and H. Chen, "Evaluating Sentiment in Financial News Articles," Decision Support Systems, Volume 53, Number 3, Pages 458-464, 2012
  • A. Abbasi, H. Chen, and Z. Zhang, “Selecting Attributes for Sentiment Classification Using Feature Relation Networks,” IEEE Transactions on Knowledge and Data Engineering, Volume 23, Number 3, Pages 447-462, 2011.
  • H. Chen, M. Chau, and S. Li, “Enterprise Risk and Security Management: Data, Text and Web Mining," Decision Support Systems, Volume 50, Number 4, Pages 949-650, 2011.
  • K. Chen, H. Lu, T. Chen, S. Li, J. Lian, and H. Chen, “Giving Context to Accounting Numbers: The Role of News Coverage,” Decision Support Systems, Volume 50, Number 4, Pages 673-679, 2011.
  • H. Chen, “Smart Market and Money,” IEEE Intelligent Systems, Volume 26, Number 6, Pages 82-84, November/December, 2011.
  • H. Chen, E. C. Huang, H. Lu, and S. Li, “AZ SmartStock: Stock Prediction with Targeted Sentiment and Life Support,” IEEE Intelligent Systems, Volume 26, Number 6, Pages 84-88, November/December, 2011.
  • D. Zimbra and H. Chen, “A Stakeholder Approach to Stock Prediction using Finance Social Media,” IEEE Intelligent Systems, Volume 26, Number 6, Pages 88-92, November/December, 2011.
  • X. Li and H. Chen, “Recommendation as Link Prediction in Bipartite Graphs: A Graph Kernel-based Machine Learning Approach,” Decision Support Systems, 2012.


  • M. Chau, C. Wong, Y. Zhou, J. Qin, and H. Chen, “Evaluating the Use of Search Engine Development Tools in IT Education,” Journal of the American Society for Information Science and Technology, Volume 61, Number 2, Pages 288-299, 2010.
  • Y. Dang, Y, Zhang, and H. Chen, “A Lexicon Enhanced Method for Sentiment Classification: An Experiment on Online Product Reviews,” IEEE Intelligent Systems, Volume 25, Number 4, Pages 46-53, 2010.
  • B. Zhu, S. Watts, and H. Chen, “Visualizing Social Network Concepts,” Decision Support Systems, Volume 49, Number 2. Pages 151-161, 2010.
  • N. Memon, J. Xu, D. Hicks, and H. Chen, “Social Network Data Mining: Research Questions, Techniques, and Applications,” Annals of Information Systems, Volume 12, Pages 1-8, 2010.
  • H. Chen, “Business and Market Intelligence 2.0,” IEEE Intelligent Systems, Volume 25, Number 1, Pages 68-71, January/February, 2010.
  • Y. Liu, Y. Chen, R. F. Lusch, H. Chen, D. Zimbra, and S. Zeng “User-Generated Content on Social Media: Predicting Market Success with Online Word-of-Mouth,” IEEE Intelligent Systems, Volume 25, Number 1, Pages 75-78, January/February, 2010.
  • H. Lu, H. Chen, T. Chen, M. Hung, and S. Li “Financial Text Mining: Supporting Decision Making Using Web 2.0 Content,” IEEE Intelligent Systems, Volume 26, Number 2, Pages 78-82, January/February, 2010.
  • H. Chen and D. Zimbra, “AI and Opinion Mining,” IEEE Intelligent Systems, Volume 25, Number 3, Pages 74-76, May/June, 2010.
  • A. Abbasi, Z. Zhang, D. Zimbra, H. Chen, and J. F. Nunamaker, “Detecting Fake Websites: The Contribution of Statistical Learning Theory,” MIS Quarterly, Volume 34, Number 3, Pages 435-461, September 2010.
  • P. Hu, F. M. Hsu, and H. Chen, “Examining Agencies’ Satisfaction with Electronic Record Management Systems: A Large-scale Survey Study,” Journal of the American Society for Information Science and Technology, 2010.
  • S. Kaza and H. Chen, “Effect of Inventor Status on Intra-Organizational Innovation Evolution,” HICSS 2009, Hawaii.
  • W. Chung, H. Chen, and E. Reid, “Business Stakeholder Analyzer: An Experiment of Classifying Stakeholders on the Web,” Journal of the American Society for Information Science and Technology, Volume 60, Number 1, Pages 59-74, 2009.
  • R. Schumaker and H. Chen, “Textual Analysis of Stock Market Prediction Using Breaking Financial News: The AZFinText System,” ACM Transactions on Information Systems, Volume 27, Number 2, April 2009.
  • R. Schumaker and H. Chen, “A Quantitative Stock Prediction System based on Financial News,” Information Processing and Management,Volume 45, Number 5, Pages 571-583, 2009.
  • H. Chen, “AI and Global Science and Technology Assessment,” IEEE Intelligent Systems, Volume 24, Number 4, Pages 68-71, July/August, 2009.
  • H. Chen, “AI, E-Government, and Politics 2.0,” IEEE Intelligent Systems, Volume 24, Number 5, Pages 64-67, September/October, 2009.
  • A. Abbasi and H. Chen, “A Comparison of Tools for Detecting Fake Websites,” IEEE Computer, Volume 42, Number 10, Pages 78-86, October 2009.
  • H. Chen, X. Li, M. Chau, Y. Ho, and C. Tseng “Using Open Web APIs in Teaching Web Mining,” IEEE Transactions on Education, Volume 52, Number 4, Pages 482-490, 2009.
  • R. Schumaker and H. Chen, “A Discrete Stock Prediction Engine based on Financial News,” IEEE Computer, Volume 43, Number 1, Pages 51-56, January 2009.
  • B. Zhu and H. Chen, “Communication Garden Systems: Visualizing a Computer-Mediated Communication Process,” Decision Support Systems, Volume 45, Number 4, Pages 778-794, 2008.
  • R. Schumaker and H. Chen, "Evaluating a News-Aware Quantitative Trader: The Effect of Momentum and Contrarian Stock Selection Strategies," Journal of the American Society for Information Science and Technology, Volume 59, Number 2, Pages 247-255, 2008.
  • Abbasi, H. Chen and J. F. Nunamaker, “Stylometric Identification in Electronic Markets: Scalability and Robustness,” Journal of Management Information Systems, Volume 25, Number 1, Pages 49-78, 2008.
  • Abbasi and H. Chen, “CyberGate: A System and Design for Text Analysis of Computer Mediated Communications,” MIS Quarterly, Volume 32, Number 4, Pages 811-837, December 2008.
  • A. Abbasi, H. Chen, S. Thoms, and T. J. Fu, "Affect Analysis of Web Forums and Blogs using Correlation Ensembles," IEEE Transactions on Knowledge and Data Engineering, 2008.
  • Z. Huang, D. Zeng, and H. Chen, "A Comparative Study of Collaborative-Filtering Recommendation Algorithms for E-Commerce," IEEE Intelligent Systems, Volume 22, Number 5, Pages 68-78, 2007.
  • M. Chau, B. Shiu, I. Chan and H. Chen, "Redips: Backlink Search and Analysis on the Web for Business Intelligence Analysis," Journal of the American Society for Information Science and Technology, Volume 58, Number 3, Pages 351-365, 2007.
  • Z. Huang, D. Zeng, and H. Chen, "Analyzing Consumer-Product Graphs: Empirical Findings and Applications in Recommendation Systems," Management Science, Volume 53, Number 7, Pages 1146-1164, July 2007.
  • Z. Huang, H. Chen, F. Guo, J. Xu, S. Wu, and W. Chen, "Expertise Visualization: An Implementation and Study based on Cognitive Fit Theory," Decision Support Systems, Volume 42, Number 3, Pages 1539-1558, December 2006.
  • W. Chung, A. Bonillas, G. Lai, W. Xi, and H. Chen, "Supporting Non-English Web Searching: An Experiment on the Spanish Business and the Arabic Medical Intelligence Portals," Decision Support Systems, Volume 42, Number 3, Pages 1697-1714, 2006.
  • Z. Huang, H. Chen, X. Li, and M. C. Roco, "Connecting NSF Funding to Patent Innovation in Nanotechnology (2001-2004)," Journal of Nanoparticle Research, Volume 8, Number 6, Pages 859-879, 2006.


  • W. Chung, H. Chen and J. F. Nunamaker, "A Visual Knowledge Map Framework for the Discovery of Business Intelligence on the Web," Journal of Management Information Systems, Volume 21, Number 4, Pages 57-84, 2005.
  • T. Ong, H. Chen, W. Sung, and B. Zhu, "NewsMap: A Knowledge Map for Online News," Decision Support Systems, Volume 39, Number 4, Pages 583-598, June, 2005.
  • P. Zhang, J. Sun, and H. Chen, "Frame-based Argumentation for Group Decision Task Generation and Identification," Decision Support Systems, Volume 39, Number 4, Pages 643-660, June, 2005.
  • Z. Huang, H. Chen, L. Yan, and M. C. Roco, "Longitudinal Nanotechnology Development (1991-2002): National Science Foundation Funding and Its Impact on Patients," Journal of Nanoparticle Research, Volume 7, Pages 343-376, 2005.
  • Z. Huang, W. Chung, and H. Chen, "A Graph Model for E-Commerce Recommender Systems," Journal of the American Society for Information Science and Technology, Volume 55, Number 3, Pages 259-274, 2004.
  • Z. Huang, H. Chen, C. J. Hsu, W. H. Chen, and S. Wu, "Credit Rating Analysis with Support Vector Machines and Neural Networks: A Market Comparative Study,"Decision Support Systems, Volume 37, Number 4, Pages 543-558, 2004.
  • H. Chen, M. C. Chau, and D. Zeng, "CI Spider: A Tool for Competitive Intelligence on the Web," Decision Support Systems, Volume 34, Number 1, Pages 1-17, December, 2002.


  • H. Chen, A. Houston, J. Yen, and J. F. Nunamaker, "Toward Intelligent Meeting Agents," IEEE Computer, Volume 29, Number 8, Pages 62-70, August, 1996.
  • R. Orwig, H. Chen, D. Vogel, and J. F. Nunamaker, “A Multi-Agent View of Strategic Planning Using Group Support Systems and Artificial Intelligence,” Group Decision and Negotiation, Volume 5, Pages 37-59, 1996.
  • R. E. Orwig, H. Chen, and J. F. Nunamaker, "A Graphical, Self-Organizing Approach to Classifying Electronic Meeting Output," Journal of the American Society for Information Science, Volume 48, Number 2, Pages 157-170, February, 1997.
  • H. Chen, O. Titkova, R. Orwig, and J. F. Nunamaker, "Information Visualization for Collaborative Computing," IEEE Computer, Volume 31, Number 8, Pages 75-82, August, 1998.
  • D. Roussinov and H. Chen, "Document Clustering for Electronic Meetings: An Experimental Comparison of Two Techniques," Decision Support Systems, Volume 27, Number 1, Pages 67-80, November 1999.
  • M. McQuaid, T. Ong, H. Chen, and J. F. Nunamaker, "Multidimensional Scaling for Group Memory Visualization," Decision Support Systems, Volume 27, Number 1-2, Pages 163-176, November 1999.


Conference Publications:

  • S. Jiang and H. Chen, “NATERGM: A Model for Examining the Role of Nodal Attributes in Dynamic Social Media Networks,” IEEE 32nd International Conference on Data Engineering (ICDE), Helsinki, Finland, May 16-20, 2016.
  • Q. Li, L. Jiang, P. Li, and H. Chen, “Tensor-based Learning for Perceiving Information-driven Stock Movements,” The Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), Austin, Texas, January 2015.
  • S. Jiang S., Q. Gao, and H. Chen, “A Computational Approach to Detecting and Assessing Sustainability-related Communities in Social Media,” In Proceedings of the 34th International Conference on Information Systems (ICIS), Milano, Italy, December 15-19, 2013.