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Frequent itemsets mining will not conducive to data analysis. Because of frequent itemsets mining produce very large amount of frequent itemsets in the case large data. Frequent closed itemsets provides a lossless frequent item sets, the smallest representation. This paper aims at the problem of shortage of the DCI_Closed algorithm in the process of mining efficiency, puts forward a kind of improved...
Nowadays, frequent item set mining is the major task in association rule mining. With the observation that the support plays an important role in mining frequent item sets, in this paper, we review the previous efficient algorithms and study the effect of different order of support in the performance of frequent item sets mining algorithms and propose our improved schedule. In our new algorithm, items...
K-means clustering is a popular conventional clustering algorithm. As it does not use the structure information of data sets, sometime the clustering result will be dissatisfied. Manifold learning algorithms can reveal the low-dimensional geometry structure of the data sets. In this paper, we combine K-means clustering algorithm with manifold learning algorithms into a coherent framework. We show...
In e-learning environment, computer-aided test-sheet composition play an important role in computer-aided testing systems. To meet the needs of multiple assessment criteria, a new test-sheet construction model was proposed. Based on the proposed model, a discrete differential evolution algorithm with effective coding strategy was designed to generate high quality test-sheets for computer-aided testing...
The cyber informatics approach to agents is defined not only by the analysis of 802.11b, but also by the technical need for red-black trees. In fact, few experts would disagree with the understanding of cache coherence, which embodies the practical principles of complexity theory. In this work, we explore an application for omniscient methodologies, which we use to verify that neural networks and...
This paper investigates the computation complexity and long resolving time problems that exist in the optimal control algorithm based on MLD (Mixed Logical Dynamical) model. Basing on polynomial matrix, an improved algorithm is presented to reduce the dimension of the inequality constraints in MLD model. The computation complexity in the optimal algorithm has been reduced greatly. The resolvinThis...
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