Abstract: Intelligent computing in large-scale systems provides systematic methodologies and tools for building complex inferential systems, which are able to adapt, mine data sets, evolve, and act in a nimble manner within major distributed environments with diverse architectures featuring multiple cores, accelerators, and high-speed networks.We believe that the papers presented in this special issue ought to serve as a reference for students, researchers, and industry practitioners interested in the evolving, interdisciplinary area of intelligent computing in large-scale systems. We very much hope that readers will find in this compendium new inspiration and ideas to enhance their own research.
Buchanan F., Capanni N. & González-Vélez H.2015. Distributed aggregation of heterogeneous web-based fine art information: enabling multi-source accessibility and curation. The Knowledge Engineering Review30, 220–236.
Gateau B., Ouedraogo M., Feltus C., Guemkam G., Danoy G., Seredynski M., Khan S. U., Khadraoui D. & Bouvry P.2015. Adopting trust and assurance as indicators for the reassignment of responsibilities in multi-agent systems. The Knowledge Engineering Review30, 187–200.
Irfan R., King C., Grages D., Ewen S., Khan S. U., Madani S., Kolodziej J., Wang L., Chen D. & Rayes A.2015. A survey on text mining in social networks. The Knowledge Engineering Review30, 157–170.
Moore P. T. & Pham H. V.2015. Personalization and rule strategies in human-centric data intensive intelligent context-aware systems. The Knowledge Engineering Review30, 140–156.
Abstract: Abstract: Intelligent computing in large-scale systems provides systematic methodologies and tools for building complex inferential systems, which are able to adapt, mine data sets, evolve, and act in a nimble manner within major distributed environments with diverse architectures featuring multiple cores, accelerators, and high-speed networks.We believe that the papers presented in this special issue ought to serve as a reference for students, researchers, and industry practitioners interested in the evolving, interdisciplinary area of intelligent computing in large-scale systems. We very much hope that readers will find in this compendium new inspiration and ideas to enhance their own research.
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Acknowledgments
The authors are grateful to all the contributors of this special issue for their willingness to work on this project. The authors thank the authors for their interesting papers, time, efforts, and their research results. Their contributions make this publication an interesting review of the recent research advances and technology development of intelligent computing for large, distributed systems. The authors also would like to express their sincere thanks to the anonymous reviewers, who have helped them ensure the quality of this issue. The authors gratefully acknowledge their time and valuable remarks and comments. Finally, special thanks to the editors of The Knowledge Engineering Review for their great support throughout the entire publication process.
