With the great diffusion of multimedia information on the web, plenty of solutions are proposed to solve the web users' cognitive overload. Despite the multitude of solutions, the web users are still looking for more and more simple assistant in web using. In this paper we present an information adaptation system using characteristics of the user. Our work aims improving access to information through recommendations made by system users with access to information. After introducing the concepts and mechanisms used by our system, we compare it with other systems in order to show the originality of our ideas.

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In this paper, we present parallel programming approaches to calculate the values of the cells in matrix's scoring used in the Smith-Waterman's algorithm for sequence alignment. This algorithm, well known in bioinformatics for its applications, is unfortunately time-consuming on a serial computer. We use formulation based on anti-diagonals structure of data. This representation focuses on parallelizable parts of the algorithm without changing the initial formulation of the algorithm. Approaching data in that way give us a formulation more flexible. To examine this approach, we encode it in OpenMP and Cuda C. The performance obtained shows the interest of our paper.