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DBSCAN is a well-known clustering algorithmwhich is based on density and is able to identify arbitraryshaped clusters and eliminate noise data. However, parallelization of DBSCAN is a challenging work because based on MPIor OpenMP environments, there exist the issues of lack of fault-tolerance and there is no guarantee that workload is balanced. Moreover, programming with MPI requires data scientists...
MicroRNAs (miRNAs) are newly discovered endogenous small non-coding RNAs (21-25nt) that target their complementary gene transcripts for degradation or translational repression. The biogenesis of a functional miRNA is largely dependent on the secondary structure of the miRNA precursor (pre-miRNA). Recently, it has been shown that miRNAs are present in the genome as the form of polycistronic transcriptional...
We present experimental results of comparing the modified K-nearest neighbor (MkNN) algorithm with support vector machine (SVM) in the prediction of condition numbers of sparse matrices. Condition number of a matrix is an important measure in numerical analysis and linear algebra. However, the direct computation of the condition number of a matrix is very expensive in terms of CPU and memory cost,...
How to control the level of knowledge disclosure and se- cure certain confidential patterns is a subtask comparable to confidential data hiding in privacy preserving data min- ing. We propose a technique to simultaneously hide data values and confidential patterns without undesirable side effects on distorting nonconfidential patterns. We use non- negative matrix factorization technique to distort...
Privacy-preserving is a major concern in the application of data mining techniques to datasets containing personal, sensitive, or confidential information. Data distortion is a critical component to preserve privacy in security-related data mining applications, such as in data mining-based terrorist analysis systems. We propose a sparsified Singular Value Decomposition (SVD) method for data distortion...
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