The Resource Space Model (RSM) offers a novel approach to organizing and managing resources by normalizing classification semantics. It emphasizes the importance of categorizing objects at various granularity levels, establishing connections between known items, and uncovering relationships between known and unknown entities. This framework aims to enhance the effectiveness of new-generation semantic data models, providing a structured method for resource management in complex data environments.
Text summarization has been studied for over a half century, but traditional methods process texts empirically and neglect the fundamental characteristics and principles of language use and understanding. Automatic summarization is a desirable technique for processing big data. This reference summarizes previous text summarization approaches in a multi-dimensional category space, introduces a multi-dimensional methodology for research and development, unveils the basic characteristics and principles of language use and understanding, investigates some fundamental mechanisms of summarization, studies dimensions on representations, and proposes a multi-dimensional evaluation mechanism. Investigation extends to incorporating pictures into summary and to the summarization of videos, graphs and pictures, and converges to a general summarization method. Further, some basic behaviors of summarization are studied in the complex cyber-physical-social space. Finally, a creative summarization mechanism is proposed as an effort toward the creative summarization of things, which is an open process of interactions among physical objects, data, people, and systems in cyber-physical-social space through a multi-dimensional lens of semantic computing. The author's insights can inspire research and development of many computing areas. The first book that proposes the method for the summarization of things in cyber-physical society through a multi-dimensional lens of semantic computing. A transformation from the traditional application-driven research paradigm into a data-driven research paradigm for creative summarization through information modeling, cognitive modeling and knowledge modeling. A multi-dimensional methodology for studying, managing, creating and applying methods
This volume presents the accepted papers for the 4th International Conference onGridandCooperativeComputing(GCC2005), heldinBeijing, China, during November 30 – December 3, 2005. The conferenceseries of GCC aims to provide an international forum for the presentation and discussion of research trends on the theory, method, and design of Grid and cooperative computing as well as their scienti? c, engineering and commercial applications. It has become a major annual event in this area. The First International Conference on Grid and Cooperative Computing (GCC2002)received168submissions. GCC2003received550submissions, from which 176 regular papers and 173 short papers were accepted. The acceptance rate of regular papers was 32%, and the total acceptance rate was 64%. GCC 2004 received 427 main-conference submissions and 154 workshop submissions. The main conference accepted 96 regular papers and 62 short papers. The - ceptance rate of the regular papers was 23%. The total acceptance rate of the main conference was 37%. For this conference, we received 576 submissions. Each was reviewed by two independent members of the International Program Committee. After carefully evaluating their originality and quality, we accepted 57 regular papers and 84 short papers. The acceptance rate of regular papers was 10%. The total acc- tance rate was 25%.
