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Abstract: v Abstract In Constraint-Based Data Mining, the task is to nd all patterns from a formal language that satisfy a speci ed constraint w.r.t. a given database. This thesis gives two novel algorithms that calculate this solution space. The rst of these methods is completely randomized and applicable to any pattern language with a partial order. It constructs the borders of the version space from within, i.e. by allowing an arbitrary sequence of pattern evaluations. The second algorithm is... (Update)
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BibTeX entry: (Update)
@misc{ fischer-version,
author = "Johannes Fischer",
title = "Version Spaces in Constraint-Based Data Mining",
url = "citeseer.ist.psu.edu/fischer03version.html" }
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[Article contains additional citations not shown here]
Documents on the same site (http://cgi.bio.ifi.lmu.de/~fischer/):
Towards Optimizing Conjunctive Inductive Queries - Fischer, De Raedt (Correct)
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