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Information Mining Processes Based on Intelligent Systems

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Recent Trends in Applied Artificial Intelligence (IEA/AIE 2013)

Abstract

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.

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García-Martínez, R., Britos, P., Rodríguez, D. (2013). Information Mining Processes Based on Intelligent Systems . In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds) Recent Trends in Applied Artificial Intelligence. IEA/AIE 2013. Lecture Notes in Computer Science(), vol 7906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38577-3_41

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  • DOI: https://doi.org/10.1007/978-3-642-38577-3_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38576-6

  • Online ISBN: 978-3-642-38577-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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