triclustering 2023.5.31.1

Triclustering and association rule mining Suffix Forest and Frequent Closed Itemset based algorithm.

triclustering-using-suffix_forest

UG Final Year Project based on Suffix Forest Based Tri-clustering

We introduce a novel data structure called a suffix-forest to design a tri-clustering algorithm. Tri-clustering is a method of unsupervised 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.