Commenced in January 2007
Paper Count: 31103
Business Intelligence for N=1 Analytics using Hybrid Intelligent System Approach
Authors: Rajendra M Sonar
Abstract:The future of business intelligence (BI) is to integrate intelligence into operational systems that works in real-time analyzing small chunks of data based on requirements on continuous basis. This is moving away from traditional approach of doing analysis on ad-hoc basis or sporadically in passive and off-line mode analyzing huge amount data. Various AI techniques such as expert systems, case-based reasoning, neural-networks play important role in building business intelligent systems. Since BI involves various tasks and models various types of problems, hybrid intelligent techniques can be better choice. Intelligent systems accessible through web services make it easier to integrate them into existing operational systems to add intelligence in every business processes. These can be built to be invoked in modular and distributed way to work in real time. Functionality of such systems can be extended to get external inputs compatible with formats like RSS. In this paper, we describe a framework that use effective combinations of these techniques, accessible through web services and work in real-time. We have successfully developed various prototype systems and done few commercial deployments in the area of personalization and recommendation on mobile and websites.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1084508Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1801
 R. Ling, and D.C. Yen, "Customer relationship management: an analysis framework and implementation strategies", Journal of Computer Information Systems, Vol. 41, No. 3, pp. 82-97, 2001.
 E. W. T. Ngai, Li Xiu, D. C. K. Chau, "Review: Application of data mining techniques in customer relationship management: A literature review and classification", Expert Systems with Applications: An International Journal, Vol. 36, No. 2, 2592-2602, 2009.
 E. W. T. Ngai, "Customer relationship management research (1992- 2002): An academic literature review and classification", Marketing Intelligence, Planning, Vol. 23. 582-605, 2005.
 J. Abbott, M. Stone, F. Buttle, "Customer relationship management in practice - a qualitative study", Journal of Database Marketing, Vol. 9 No.1, pp.24-34, 2001.
 S.L. Pan and J.N. Lee, "Using e-CRM for a unified view of the customer", Communications of the ACM, 46, (4), 95-99, 2003.
 C.K. Prahalad, M.S. Krishnan, The new age of innovation: Driving Cocreated Value Through Global Networks, Tata McGraw Hill, New Delhi, 2008
 Don Tapscott , Anthony D. Williams, Wikinomics: How Mass Collaboration Changes Everything, Portfolio, 2006
 http://www.trai.gov.in/ accessed on 25 June 2009.
 http://www.rbi.org.in/ accessed on 25 June 2009.
 E. Turban , J. Aronson , Ting-Peng Liang, Decision Support Systems and Intelligent Systems (7th Edition), Prentice-Hall, Inc., Upper Saddle River, NJ, 2004.
 R. Bergmann, K-D Althoff, S. Breem, M. Goker, M. Manago, R. Traphoner, Developing Industrial Case-Based Reasoning Applications, 2nd Ed., Springer, Berlin, 2003.
 L. Medsker, Hybrid intelligent systems, Kluwer Academic Publishers, Boston, 1995.
 S. Goonatilake and S. Khebbal, ed. Intelligent Hybrid System, John Wiley and Sons, 1995.
 E. Corchado, J. Corchado, A. Abraham, Innovations in Hybrid Intelligent System, Springer, 2008.
 http://www.w3.org/XML/ accessed on 25 June 2009.
 W. Richardson, "The ABCs of RSS". Technology & Learning, Issue 10, 20-24, May 2005.
 R.M. Sonar, "An Enterprise Intelligent System Development and Solution Framework", International journal of applied science, engineering and technology, Vol. 4, No. 1, 31-35, 2008, Available at http://www.waset.org/journals/ijaset/v4/v4-1-6.pdf accessed on 25 June 2009.
 http://www.ikenstudio.com accessed on 25 June 2009.
 J. Kolodner, J., Case-Based Reasoning, Morgan Kaufmann, San Mateo, CA, 1993.
 A. Aamodt, E. Plaza, "Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches", AI Communications, Vol. 7:1, 39-52, 1994.
 A. Felfernig, G. Friedrich, L. Schmidt-Thieme, "Introduction to the Recommender Systems", IEEE Intelligent Systems Special Issue, 22(3), 18-21, 2007.
 A. Felfernig, R. Burke, "Constraint-based recommender systems: technologies and research issues", ICEC '08: Proceedings of the 10th international conference on Electronic commerce, New York, NY, USA, ACM, 1-10, 2008.
 G. Adomavicius, A. Tuzhilin, "Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions", IEEE Transactions on Knowledge and Data Engineering, 17(6), 734-749, 2005.
 R. Burke, 2007. "Hybrid web recommender systems", The Adaptive Web: Methods and Strategies of Web Personalization, 377-408, Heidelberg, Germany, Springer, 2007.
 M. Balabanovic, Y. Shoham, "Fab: Content-Based, Collaborative Recommendation", Communications of ACM, Vol. 40, No. 3, 66-72, 1997.
 R. Burke, "Knowledge-Based Recommender Systems", Encyclopedia of Library and Information Systems, A. Kent, ed., Vol. 69, Supplement 32, Marcel Dekker, 2000.
 A. Felfernig, "Koba4MS: Selling Complex Products and Services Using Knowledge-Based Recommender Technologies", Proc of the Seventh IEEE International Conference on E-Commerce Technology, July 19-22, 92-100, 2005.
 N. Mirzadeh, F. Ricci, M. Bansal, "Feature Selection Methods for Conversational Recommender Systems", IEEE International Conference on e-Technology, e-Commerce, and e-Service (EEE-05), Hongkong, 772-777, 2005.
 M. Godse, R. Sonar, A. Jadhav, "A Hybrid Approach for Knowledgebased Product Recommendation", Communications in Computer and Information Science, Springer, Vol. 31, 268-279, 2009.
 A. Jadhav, R. Sonar, "An Integrated Rule-based and Case-based Reasoning Approach for Selection of the Software Packages", Communications in Computer and Information Science, Springer- Verlag, Vol. 31, 280-291, 2009.
 http://www.ikensolutions.com/files/en/Mooga_casestudySony.pdf accessed on 25 June 2009.