Graphs have so many applications in real world problems. When we deal with huge volume of data, analyzing data is difficult or sometimes impossible. In big data problems, clustering data is a useful tool for data analysis. Singular value decomposition(SVD) is one of the best algorithms for clustering graph but we do not have any choice to select the number of clusters and the number of members ...

Vehicular ad-hoc network (VANET) is an important component of intelligent transportation systems, in which vehicles are equipped with on-board computing and communication devices which enable vehicle-to-vehicle communication. Consequently, with regard to larger communication due to the greater number of vehicles, stability of connectivity would be a challenging problem. Clustering technique as ...

Nowadays, we have to deal with a large quantity of unstructured data, produced by a number of sources. For example, clustering web pages is essential to getting structured information in response to user queries. In this paper, we intend to test the results of a new clustering technique – clustering by compression – when applied to heterogeneous sets of data. The clustering by compression proce...

Clustering has been an important tool for extracting underlying gene expression patterns from massive microarray data. However, most of the existing clustering methods cannot automatically separate noise genes, including scattered, singleton and mini-cluster genes, from other genes. Inclusion of noise genes into regular clustering processes can impede identification of gene expression patterns....

background: selecting the correct statistical test and data mining method depends highly on the measurement scale of data, type of variables, and purpose of the analysis. different measurement scales are studied in details and statistical comparison, modeling, and data mining methods are studied based upon using several medical examples. we have presented two ordinal–variables clustering exampl...

To address the problem of the difficulty of traditional clustering methods to adapt to online clustering of streaming data and on the basis of the research on the evolutionary clustering method (ECM), this paper proposes a Davies-Bouldin index evolving clustering method for streaming data clustering (DBIECM). This method has improved the updating process of the clustering center and the radius ...

In this paper, we devise an efficient algorithm for clustering market-basket data items. Market-basket data analysis has been well addressed in mining association rules for discovering the set of large items which are the frequently purchased items among all transactions. In essence, clustering is meant to divide a set of data items into some proper groups in such a way that items in the same g...