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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Towards Incremental Knowledge Warehousing and Mining
verfasst von : Habiba Drias, Asma Aouichat, Aicha Boutorh
Erschienen in: Distributed Computing and Artificial Intelligence
Verlag: Springer Berlin Heidelberg
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In this paper, we propose new ideas around the concepts of knowledge warehousing and mining. More precisely, we focus on the mining part and develop original approaches for incremental clustering based on k-means for knowledge bases. Instead of addressing the prohibitive amounts of knowledge, the latter is gradually exploited by packets in order to reduce the problem complexity. We introduce original algorithms named ICPK/k-means for
Incremental Clustering by Packets of Knowledge
, ICPKG/k-means for
Incremental Algorithm by Packets of Knowledge and Grouping of clusters
for determining the number of desired clusters, LICPK/k-means for
Learning Incremental Clustering by Packets of Knowledge
and LIGPKG/k-means for
Learning Incremental Clustering by Packets of Knowledge and Grouping of clusters
for handling the clustering of large amount of knowledge. Experimental results prove the effectiveness of our algorithms.