Large, high dimensional data spaces, are still a challenge for current data clustering methods. Frequent Termset (FTS) clustering is a technique developed to cope with these chall...
Latent semantic indexing (LSI) is a well-known unsupervised approach for dimensionality reduction in information retrieval. However if the output information (i.e. category labels...
Several advanced techniques have been proposed for data clustering and many of them have been applied to gene expression data, with partial success. The high dimensionality and the...
Dimension reduction is a critical data preprocessing step for many database and data mining applications, such as efficient storage and retrieval of high-dimensional data. In the ...
Jieping Ye, Qi Li, Hui Xiong, Haesun Park, Ravi Ja...
Clustering is one of the most important tasks performed in Data Mining applications. This paper presents an e cient SQL implementation of the EM algorithm to perform clustering in...