An evolutionary factor analysis computation for mining website structures

This paper explores website link structure considering websites as interconnected graphs and analyzing their features as a social network. Two networks have been extracted for representing websites: a domain network containing subdomains or external domains linked through the website and a page network containing webpages browsed from the root domain. Factor analysis provides the statistical methodology to adequately extract the main website profiles in terms of their internal structure. However, due to the large number of indicators, the task of selecting a representative subset of indicators becomes unaffordable. A genetic search of an optimum subset of indicators is proposed in this paper, selecting a multiobjective fitness function based on factor analysis results. The optimum solution provides a coherent and relevant categorization of website profiles, and highlights the possibilities of genetic algorithms as a tool for discovering new knowledge in the field of web miningMinisterio de Educación y Ciencia DPI2007- 60128Junta de Andalucía. Consejería de Innovación, Ciencia y Empresa P07-TIC-0262

Recent Advances in Graph Partitioning

We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions

New Knowledge for Old Regions? The Case of the Software Park Hagenberg in the Traditional Industrial Region of Upper Austria

This paper seeks to enhance our understanding about the opportunities and limits of new path creation in traditional regional innovation systems. Due to their inherited historical legacies, such systems are usually thought of being ill-equipped to give rise to high-tech or knowledge intensive activities. Departing from recent insights on research concerned with the transformation of innovation systems and evolutionary economic geography we identify in a conceptual way enabling and constraining factors for the rise of new development paths in traditional regions. Empirically, we focus on the case of the “Software Park Hagenberg†(SPH) located in the old industrial region of Upper Austria. We examine key events triggering the emergence and subsequent evolution of the SPH and explore the role of the RIS in shaping the development trajectory of the SPH. Moreover, applying social network analysis tools, we investigate the pattern of networking between firms, research organisations and educational bodies within the SPH and we provide some evidence on the diffusion of knowledge and innovation generated though these interactions throughout the regional economy.

Computational predictions of energy materials using density functional theory

In the search for new functional materials, quantum mechanics is an exciting starting point. The fundamental laws that govern the behaviour of electrons have the possibility, at the other end of the scale, to predict the performance of a material for a targeted application. In some cases, this is achievable using density functional theory (DFT). In this Review, we highlight DFT studies predicting energy-related materials that were subsequently confirmed experimentally. The attributes and limitations of DFT for the computational design of materials for lithium-ion batteries, hydrogen production and storage materials, superconductors, photovoltaics and thermoelectric materials are discussed. In the future, we expect that the accuracy of DFT-based methods will continue to improve and that growth in computing power will enable millions of materials to be virtually screened for specific applications. Thus, these examples represent a first glimpse of what may become a routine and integral step in materials discovery