Query recommender systems give users hints on possible interesting queries relative to their information needs. Most query recommenders are based on static knowledge models built on the basis of past user behaviors recorded in query logs. These models should be periodically updated, or rebuilt from scratch, to keep up with the possible variations in the interests of users. We study query recomm...

The Genomic Median Problem is an optimization problem inspired by a biological issue: it aims at finding the genome organization of the common ancestor to multiple living species. It is formulated as the search for a genome that minimizes some distance measure among given genomes. Several attempts have been made at solving the problem. These range from simple heuristic methods to a stochastic l...

The set-covering problem is an interesting problem in computational complexity theory. In [1], the setcovering problem has been proved to be NP hard and a greedy heuristic algorithm is presented to solve the problem. In [2], the set-covering problem is found to be equivalent to the problem of identifying redundant search engines on the Web, and finding efficient and effective practical algorith...

The paper presents a study of autonomous face recognition systems based on high performance DSP, so called Media Processors and on Field Programmable Gate Array (FPGA) devices. An overview of the most powerful Media Processors and FPGAs available today is followed by an analysis of the common features of the face recognition algorithms used to implement an application. The paper presents also a...

The purpose of this paper is to establish some guidelines for designing effective Estimation of Distribution Algorithms (EDAs). These guidelines aim at balancing intensification and diversification in EDAs. Most EDAs are able to maintain some important linkages among variables. This advantage, however, may lead to the premature convergence of EDAs since the probabilistic models no longer genera...

This paper focuses on developing effective and efficient algorithms for compressing scientific simulation data computed on structured and unstructured grids. A paradigm for lossy compression of this data is proposed in which the data computed on the grid is modeled as a graph, which gets decomposed into sets of vertices which satisfy a user defined error constraint ǫ. Each set of vertices is re...

Medical image reconstruction from projections is computationally intensive task that demands solutions for reducing the processing delay in clinical diagnosis applications. This paper analyzes reconstruction methods combined with preand post-filtering for Single Photon Emission Computed Tomography (SPECT) in terms of convergence speed and image quality. The evaluation is performed by means of a...