Triclustering and association rule mining using Suffix Forest and Frequent Closed Itemset based algorithm.
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triclustering-using-suffix_forest
We introduce a novel data structure called a suffix-forest to design a tri-clustering algorithm. Tri-clustering is a method of data analysis used to find patterns of interest in three-dimensional data.
This is a new approach for association rule mining and bi-clustering using formal concept analysis. The approach is called FIST and is based on the frequent closed itemsets framework, requiring a unique scan of the database. FIST uses a new suffix tree-based data structure to reduce memory usage and improve extraction efficiency. Experiments show that FIST's memory requirements and execution times are in most cases equivalent to frequent closed itemsets-based algorithms and lower than frequent itemsets-based algorithms.
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