In literature studies, high-dimensional data reduces the efficiency of clustering algorithms and maximises execution time. Therefore, in this paper, we propose an approach called a BV-kmeans (Bayesian Vectorisation along with k-means) that aims to improve document representation models for text...

This work studies the theoretical rules of feature selection in linear discriminant analysis (LDA), and a new feature selection method is proposed for sparse linear discriminant analysis. An l1 minimization method is used to select the important features from which the LDA will be constructed....

Classifying land cover via satellite imagery is an important problem in geographical studies. This paper presents a maximum a posteriori (MAP) land-cover classifier for multiband satellite data. The method uses the Markov random field model. The MAP estimation is carried out via iterated...

The electronic mail (email) is nowadays an essential communication service being widely used by most Internet users. One of the main problems affecting this service is the proliferation of unsolicited messages (usually denoted by spam) which, despite the efforts made by the research community,...

Searching for information about individual entities such as persons, locations, events, is an important activity in Internet search today, and is in its core a very semantic-oriented task. Several ways for accessing such information exist, but for locating entity-specific information, search...