Special Issue: Web 2.0, Semantics, Knowledge and Grid

With the massive participations of worldwide developers and users as well as enabling collaboration and social networks, Web 2.0 is significantly influencing the development of the Web, Semantic Web and Grid by aiming at a powerful and harmonious interconnection environment. The study of the futureWeb concerns the exploration of the laws among large-scale and expanding resources such as the formation of community and effective knowledge sharing, the semantics facilitating various interactions (between human, between machines and between human and machine) the scalable infrastructure and applications. This special issue is to reflect the up-to-date progresses of research on the future Web. It contains eight papers selected mainly from the third International Conference on Semantics, Knowledge and Grid [1], which emphasizes on promoting cross-area research. Web mining and community discovery play an important role in supporting intelligent Web applications. Zhang and Xu [2] introduce a set of Web mining methods based on various available information on the Web, including Web document contents, hyperlink analysis, user access logs and semantic analysis. Several key Web clustering algorithms are studied, including a latent linkage information algorithm for finding relevant pages and a Web page clustering algorithm based on the defined concept of Web page correlation. Pierce et al. [3] introduce the application of Web 2.0 in the following scenarios: client-side JavaScript libraries for building and composing Grid services, integrating server-side portlets with ‘rich client’ AJAX tools and Web services for analyzing a global positioning system’s data, building and analyzing folksonomies of scientific user communities through social bookmarking, and applying microformats and GeoRSS to problems in scientific metadata description and delivery. The future Web and Grid need to combine different models and techniques to provide users with more accessible services and resources. Dillon et al. [4] discuss three important computing paradigms including service-oriented computing, Grid computing and Web 2.0. An abstracted distributed computing model is introduced and a Grid architecture GRIDspace is discussed. Semantic Web plays an important role in making the description of Web resources more machineunderstandable, which can be used as the basic datamodel and querymodel to support heterogeneous resource management on Semantic Grid. Babik and Hluchy present an architecture to support efficient resource description, query processing and logic reasoning based on a subset of Semantic Web language [5]. The system combines a tableau algorithm with a resolution-based reasoning