This paper deals with the application of Data Mining in the education sector. Generally the benefits of Data Mining are taken in the commercial fields. The study given, proposed a quiet different field where we can use the Data Mining and enhance the quality of education. In the given paper the performance of an institute students were studied. The study takes the performance of students in the...

This letter presents K-P-Means, a novel approach for hyperspectral endmember estimation. Spectral unmixing is formulated as a clustering problem, with the goal of K-P-Means to obtain a set of “purified” hyperspectral pixels to estimate endmembers. The K-P-Means algorithm alternates iteratively between two main steps (abundance estimation and endmember update) until convergence to yield final en...

A basic belief assignment can have up to 2 focal elements, and combining them with a simple conjunctive operator will need O(2) operations. This article proposes some techniques to limit the size of the focal sets of the bbas to be combined while preserving a large part of the information they carry. The first section revisits some well-known definitions with an algorithmic point of vue. The se...

We present a study of the clustering properties of medical publications for the aim of Evidence Based Medicine summarisation. Given a dataset of documents that have been manually assigned to groups related to clinical answers, we apply K-Means clustering and verify that the documents can be clustered reasonably well. We advance the implications of such clustering for natural language processing...

We present a new similarity measure between a single shape and a shape group as a basis for shape clustering following the paradigm of context dependent shape comparison: clusters are generated in the context of a reference shape, defined by the query shape it is compared to. Tightly coupled, the distance measure is the basis for a soft k-means like framework to achieve robust clustering. Succe...

Nowadays melanoma is one of the most important cancers to study due to its social impact. This dermatologic cancer has increased its frequency and mortality during last years. In particular, mortality is around twenty percent in non early detected ones. For this reason, the aim of medical researchers is to improve the early diagnosis through a best melanoma characterization using pattern matchi...

Internet crimes are now increasing. In a row with many crimes using information technology, in particular those using Internet, some crimes are often carried out in the form of attacks that occur within a particular agency or institution. To be able to find and identify the types of attacks, requires a long process that requires time, human resources and utilization of information technology to...

In this paper we describe two unsupervised representations of prosodic sequences based on k-means and Dirichlet Process Gaussian Mixture Model (DPGMM) clustering. The clustering algorithms are used to infer an inventory of prosodic categories over automatically segmented syllables. A tri-gram model is trained over these sequences to characterize speech. We find that DPGMM clusters show a greate...

Silhouette is one of the most popular and effective internal measures for the evaluation of clustering validity. Simplified Silhouette is a computationally simplified version of Silhouette. However, to date Simplified Silhouette has not been systematically analysed in a specific clustering algorithm. This paper analyses the application of Simplified Silhouette to the evaluation of k-means clust...

Clustering is a data mining activity that aims to differentiate groups inside a given set of objects, with respect to a set of relevant attributes of the analyzed objects. Generally, existing clustering methods, such as k-means algorithm, start with a known set of objects, measured against a known set of attributes. But there are numerous applications where the attribute set characterizing the ...