Hoang Chi Thanh

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Building a high accuracy classifier for classification is a problem in real applications. One high accuracy classifier used for this purpose is based on association rules. In the past, some researches showed that classification based on association rules (or class-association rules – CARs) has higher accuracy than that of other rule-based methods, such as(More)
The subsequence matching in large time-series databases has been being an interesting problem. Many methods have been proposed that cope with this problem in an adequate extend. One of good ideas is reducing properly the dimensionality of time-series data. In this paper, we propose a method to reduce the dimensionality of high-dimensional time-series data.(More)
Permutations of a set are used in many practical problems. There are some algorithms for generating permutations of a set, e.g. a reverse alphabetical order algorithm, an algorithm based on adjacent transpositions, an algorithm determining permutations from their reductions... But these algorithms are rather long and difficult to parallelize. In this paper(More)
In this paper, we propose a new method for mining class-association rules using a tree structure. Firstly, we design a tree structure for storing frequent itemsets of datasets. Some theorems for pruning nodes and computing information in the tree are then developed. We then propose an efficient algorithm for mining CARs based on them. Experimental results(More)
The subsequence matching in a large time-series database has been an interesting problem. Many methods have been proposed that cope with this problem in an adequate extent. One of the good ideas is reducing properly the dimensionality of time-series data. In this paper, we propose a new method to reduce the dimensionality of high-dimensional time-series(More)