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» Hierarchical Document Clustering using Frequent Itemsets
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SDM
2003
SIAM
134views Data Mining» more  SDM 2003»
13 years 6 months ago
Hierarchical Document Clustering using Frequent Itemsets
A major challenge in document clustering is the extremely high dimensionality. For example, the vocabulary for a document set can easily be thousands of words. On the other hand, ...
Benjamin C. M. Fung, Ke Wang, Martin Ester
ICDM
2006
IEEE
132views Data Mining» more  ICDM 2006»
13 years 11 months ago
High Quality, Efficient Hierarchical Document Clustering Using Closed Interesting Itemsets
High dimensionality remains a significant challenge for document clustering. Recent approaches used frequent itemsets and closed frequent itemsets to reduce dimensionality, and to...
Hassan H. Malik, John R. Kender
CAEPIA
2003
Springer
13 years 10 months ago
Text Mining Using the Hierarchical Syntactical Structure of Documents
One of the most important tasks for determining association rules consists of calculating all the maximal frequent itemsets. Specifically, some methods to obtain these itemsets hav...
Roxana Dánger, José Ruiz-Shulcloper,...
KAIS
2006
164views more  KAIS 2006»
13 years 4 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis