Semi-supervised learning techniques: k-means clustering in OODB fragmentation

A.S. Darabant, A. Campan
Second IEEE International Conference on Computational Cybernetics, 2004. ICCC 2004.  
Vertical and horizontal fragmentation are central issues in the design process of Distributed Object Based Systems. A good fragmentation scheme followed by an optimal allocation could greatly enhance performance in such systems, as data transfer between distributed sites is minimized. In this paper we present a horizontal fragmentation approach that uses the k-means AI clustering method for partitioning object instances into fragments. Our new method applies to existing databases, where
more » ... cs are already present. We model fragmentation input data in a vector space and give different object similarity measures together with their geometrical interpretations. We provide quality and performance evaluations using a partition evaluator function.
doi:10.1109/icccyb.2004.1437742 fatcat:uw552ficozefxjasno52rnsa24