Information Mining Processes Based on Intelligent Systems

Business Intelligence offers an interdisciplinary approach (within which is Information Systems), that taking all available information resources and using of analytical and synthesis tools with the ability to transform information into knowledge, focuses on generating knowledge that contributes to the management decision-making and generation of strategic plans in organizations. Information Mining is the sub-discipline of information systems which supports business intelligence tools to transform information into knowledge. It has defined as the search for interesting patterns and important regularities in large bodies of information. We address the need to identify information mining processes to obtain knowledge from available information. When information mining processes are defined, we may decide which data mining algorithms will support the information mining processes. In this context, this paper proposes a characterization of the information mining process related to the following business intelligence problems: discovery of rules of behavior, discovery of groups, discovery of significant attributes, discovering rules of group membership and weight of rules of behavior or rules of group memberships.

[1]  David Maxwell Chickering,et al.  Learning Bayesian Networks: The Combination of Knowledge and Statistical Data , 1994, Machine Learning.

[2]  Max Bramer,et al.  Artificial Intelligence in Theory and Practice II , 2009 .

[3]  Matteo Golfarelli,et al.  Beyond data warehousing: what's next in business intelligence? , 2004, DOLAP '04.

[4]  Jan Mendling,et al.  Business Process Intelligence , 2009, Handbook of Research on Business Process Modeling.

[5]  J. Ross Quinlan,et al.  Learning logical definitions from relations , 1990, Machine Learning.

[6]  Philip S. Yu,et al.  Data Mining: An Overview from a Database Perspective , 1996, IEEE Trans. Knowl. Data Eng..

[7]  Jay F. Nunamaker,et al.  A Visual Framework for Knowledge Discovery on the Web: An Empirical Study of Business Intelligence Exploration , 2005, J. Manag. Inf. Syst..

[8]  Paola Britos,et al.  Pedagogical Protocols Selection Automatic Assistance , 2008, IEA/AIE.

[9]  Ali S. Hadi,et al.  Finding Groups in Data: An Introduction to Chster Analysis , 1991 .

[10]  Ryszard S. Michalski,et al.  A theory and methodology of inductive learning , 1993 .

[11]  Teuvo Kohonen,et al.  Self-Organizing Maps , 2010 .

[12]  Yeuvo Jphonen,et al.  Self-Organizing Maps , 1995 .

[13]  Paola Britos,et al.  Patterns in Temporal Series of Meteorological Variables Using SOM & TDIDT , 2006, IFIP AI.

[14]  Paola Britos,et al.  Bayesian Networks Optimization Based on Induction Learning Techniques , 2008, IFIP AI.

[15]  Paola Britos,et al.  Detecting Unusual Changes of Users Consumption , 2008, IFIP AI.

[16]  Ivan Bratko,et al.  Machine Learning and Data Mining; Methods and Applications , 1998 .

[17]  Andreas Rudolph,et al.  Techniques of Cluster Algorithms in Data Mining , 2002, Data Mining and Knowledge Discovery.

[18]  Efraim Turban,et al.  Business Intelligence: Second European Summer School, eBISS 2012, Brussels, Belgium, July 15-21, 2012, Tutorial Lectures , 2013 .

[19]  J. R. Quinlan.  Learning Logical Definitions from Relations , 1990 .

[20]  Paola Britos,et al.  Detection of Breast Lesions in Medical Digital Imaging Using Neural Networks , 2006, IFIP PPAI.

[21]  Paola Britos,et al.  Requirements Elicitation in Data Mining for Business Intelligence Projects , 2008, Advances in Information Systems Research, Education and Practice.

[22]  M. Abásolo.  Identification of MPEG-4 FDP Patterns in Human Faces using Data-Mining Techniques , 2005 .

[23]  D. Rodriguez,et al.  Work in progress - programming misunderstandings discovering process based on intelligent data mining tools , 2008, 2008 38th Annual Frontiers in Education Conference.

[24]  Richard E. Neapolitan,et al.  Learning Bayesian networks , 2007, KDD '07.

[25]  D. E. Avison.  Advances in Information Systems Research, Education and Practice - IFIP 20th World Computer Congress, TC 8, Information Systems, September 7-10, 2008, Milano, Italy , 2008, Advances in Information Systems Research, Education and Practice.

[26]  Dimitris Plexousakis,et al.  A Formal Model for Business Process Modeling and Design , 2000, CAiSE.

[27]  Hsinchun Chen,et al.  The World Wide Web Presents Significant Opportunities Redips: Backlink Search and Analysis on the Web for Business Intelligence Analysis , 2006 .

[28]  Solomon Negash,et al.  Platforms for Business Intelligence , 2008 .