Jawad Ashraf

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— Text document clustering is an important issue in the field of information retrieval and web mining. Huge amount of text documents are needed to be clustered so that search engines can retrieve these documents efficiently and effectively. In this paper we present a novel approach for clustering text documents based on Maximal Frequent Item-set (MFI). Our(More)
Frequent itemsets (FIs) mining is a prime research area in association rule mining. The customary techniques find FIs or its variants on the basis of either support threshold value or by setting two generic parameters, i.e., N (topmost itemsets) and $$K_\mathrm{{max}}$$ K max (size of the itemsets). However, users are unable to mine the absolute desired(More)
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