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Deep Model Guided Data Analysis

  • Yannic Ole Kropp
  • Bernhard Thalheim
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 822)

Abstract

Data mining is currently a well-established technique and supported by many algorithms. It is dependent on the data on hand, on properties of the algorithms, on the technology developed so far, and on the expectations and limits to be applied. It must be thus matured, predictable, optimisable, evolving, adaptable and well-founded similar to mathematics and SPICE/CMM-based software engineering. Data mining must therefore be systematic if the results have to be fit to its purpose. One basis of this systematic approach is model management and model reasoning. We claim that systematic data mining is nothing else than systematic modelling. The main notion is the notion of the model in a variety of forms, abstraction and associations among models.

Keywords

Data mining Modelling Models Framework Deep model Normal model Modelling matrix 

Notes

Acknowledgement

This research was supported by the CRC 1266 ‘Scales of Transformation - Human-Environmental Interaction in Prehistoric and Archaic Societies’ which is funded by the DFG. We thank both institutions for enabling this work. We are also very thankful for the fruitful discussions with the members of the CRC.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceChristian Albrechts University KielKielGermany

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