Agents for Searching Rules in Civil Engineering Data Mining

Authors:
Janusz Kasperkiewicz;Maria Marks
Affiliations:
Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland 00-049;Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland 00-049
Venue:
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part III
Year:
2008

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A survey of interestingness measures for knowledge discovery

The Knowledge Engineering Review
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)

Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)

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Abstract

The software agents are applied for a remote search of information. It seems natural that to analyse such information machine learning routines should be built-in into an agent system. After finding and processing the data the generated rules will be evaluated by means of so called interestingness measures, and only the best rules should be returned to the user.The paper presents situation in civil engineering data processing, as a suggestion for designers of intelligent software tools, to work out difficult but much needed procedures that should be implemented into autonomous agent system, intended for retrieving special kind of information searched for example by materials technologists.A simple architecture for an agent system is suggested without, however, getting into any technical details on how the elements of such system should be constructed.