Abstract
Generalization lattices encode domain knowledge relevant to generalization. They provide a convenient framework for data visualization during user-guided exploration and for automated guidance during independent exploration. To reduce the size of a generalization lattice for an individual attribute, we define six types of pruning. Then we consider the generalization space defined by the cross product of lattices for several attributes. To increase the relevance of the data exploration results, we define five additional types of pruning. An interactive, web-based system for visualizing the generalization space allows the user to interactively guide the data exploration process.
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Keywords
- Knowledge Discovery
- Generalization Relation
- Virtual Reality Modelling Language
- Generalization Lattice
- Automate Guidance
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 1998 Springer-Verlag Berlin Heidelberg
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Hamilton, H.J., Hilderman, R.J., Li, L., Randall, D.J. (1998). Generalization lattices. In: Żytkow, J.M., Quafafou, M. (eds) Principles of Data Mining and Knowledge Discovery. PKDD 1998. Lecture Notes in Computer Science, vol 1510. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0094835
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DOI: https://doi.org/10.1007/BFb0094835
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