Summarization Techniques for Pattern Collections in Data Mining

Details Summarization Techniques for Pattern Collections in Data Mining Summarization Techniques for Pattern Collections in Data Mining

2005-05-26

arxiv.org/abs/cs/0505071v1

Computer Science

Databases

PhD Thesis, Department of Computer Science, University of Helsinki

Scientific paper

Discovering patterns from data is an important task in data mining. There exist techniques to find large collections of many kinds of patterns from data very efficiently. A collection of patterns can be regarded as a summary of the data. A major difficulty with patterns is that pattern collections summarizing the data well are often very large. In this dissertation we describe methods for summarizing pattern collections in order to make them also more understandable. More specifically, we focus on the following themes: 1) Quality value simplifications. 2) Pattern orderings. 3) Pattern chains and antichains. 4) Change profiles. 5) Inverse pattern discovery.

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