In order to address the study of complex systems,the detection of patterns in their dynamics could play a key role in understanding their evolution.In particular,global patterns are required to detect emergent concept...In order to address the study of complex systems,the detection of patterns in their dynamics could play a key role in understanding their evolution.In particular,global patterns are required to detect emergent concepts and trends,some of them of a qualitative nature.Formal concept analysis(FCA) is a theory whose goal is to discover and extract knowledge from qualitative data(organized in concept lattices).In complex environments,such as sport competitions,the large amount of information currently available turns concept lattices into complex networks.The authors analyze how to apply FCA reasoning in order to increase confidence in sports predictions by means of detecting regularities from data through the management of intuitive and natural attributes extracted from publicly available information.The complexity of concept lattices-considered as networks with complex topological structure- is analyzed.It is applied to building a knowledge based system for confidence-based reasoning,which simulates how humans tend to avoid the complexity of concept networks by means of bounded reasoning skills.展开更多
Research on computer architecture and systems is typically driven by technologies and applications. Big data has emerged as an important application domain which has shown its huge impact on scientific research, busin...Research on computer architecture and systems is typically driven by technologies and applications. Big data has emerged as an important application domain which has shown its huge impact on scientific research, business, and society. Big data is known for its large volume, high velocity, and a variety of formats. The collection, storage, retrieval, processing and visualization of big data issue many challenges to computer architecture and systems. On the other hand, new computer architecture and system technologies enable people to handle larger and more complex data more efficiently.展开更多
Edge network and edge cloud are important for both users and service providers in the mobile era. Driven by two radical changes recently, rapidly increasing fog computing and pervasive mobile devices, the design space...Edge network and edge cloud are important for both users and service providers in the mobile era. Driven by two radical changes recently, rapidly increasing fog computing and pervasive mobile devices, the design space of edge network and edge cloud is jointly affected by the application/service characteristics, users＇ social and mobility behaviors, and the deployment of network and cloud infrastructure. The design of edge network and edge cloud can benefit from the data-driven intelligence.展开更多
Research on computer architecture and systems is typically driven by technology and applications. Emerging technologies, such as non-volatile memory, brain-inspired computing, are shaping the future of computing. Howe...Research on computer architecture and systems is typically driven by technology and applications. Emerging technologies, such as non-volatile memory, brain-inspired computing, are shaping the future of computing. However, it is still at its early stage to use these technologies to build computer systems.展开更多
Research on computer network and distributed systems has been driven by emerging technologies and applica- tions. Big data has emerged as an important research topic and application domain, and has been known for its ...Research on computer network and distributed systems has been driven by emerging technologies and applica- tions. Big data has emerged as an important research topic and application domain, and has been known for its volume, velocity, variety, and veracity. It is challenging the conventional design in computer networking and dis- tributed computing, ranging from transmission, storage, processing, and system. This special section is an effort to promote research to address the big data challenges from the networking and distributed computing perspectives.展开更多
The Computational Visual Media （CVM） Conference series is intended to provide a major international forum for exchanging novel research ideas and significant practical computational methods which either underpin or ...The Computational Visual Media （CVM） Conference series is intended to provide a major international forum for exchanging novel research ideas and significant practical computational methods which either underpin or apply visual media. The primary rationale is to target cross-disciplinary research which amalgamates aspects of computer graphics, computer vision, machine learning, image processing, video processing, visualization and geometric computing. The main topics of interest to CVM include classification, composition, retrieval, synthesis, and understanding of visual media.展开更多
基金supported by the TIN2009-09492 project of the Spanish Ministry of Science and InnovationExcellence project TIC-6064 of Junta de Andalucia co-financed by FEDER funds
文摘In order to address the study of complex systems,the detection of patterns in their dynamics could play a key role in understanding their evolution.In particular,global patterns are required to detect emergent concepts and trends,some of them of a qualitative nature.Formal concept analysis(FCA) is a theory whose goal is to discover and extract knowledge from qualitative data(organized in concept lattices).In complex environments,such as sport competitions,the large amount of information currently available turns concept lattices into complex networks.The authors analyze how to apply FCA reasoning in order to increase confidence in sports predictions by means of detecting regularities from data through the management of intuitive and natural attributes extracted from publicly available information.The complexity of concept lattices-considered as networks with complex topological structure- is analyzed.It is applied to building a knowledge based system for confidence-based reasoning,which simulates how humans tend to avoid the complexity of concept networks by means of bounded reasoning skills.
文摘Research on computer architecture and systems is typically driven by technologies and applications. Big data has emerged as an important application domain which has shown its huge impact on scientific research, business, and society. Big data is known for its large volume, high velocity, and a variety of formats. The collection, storage, retrieval, processing and visualization of big data issue many challenges to computer architecture and systems. On the other hand, new computer architecture and system technologies enable people to handle larger and more complex data more efficiently.
文摘Edge network and edge cloud are important for both users and service providers in the mobile era. Driven by two radical changes recently, rapidly increasing fog computing and pervasive mobile devices, the design space of edge network and edge cloud is jointly affected by the application/service characteristics, users＇ social and mobility behaviors, and the deployment of network and cloud infrastructure. The design of edge network and edge cloud can benefit from the data-driven intelligence.
文摘Research on computer architecture and systems is typically driven by technology and applications. Emerging technologies, such as non-volatile memory, brain-inspired computing, are shaping the future of computing. However, it is still at its early stage to use these technologies to build computer systems.
文摘Research on computer network and distributed systems has been driven by emerging technologies and applica- tions. Big data has emerged as an important research topic and application domain, and has been known for its volume, velocity, variety, and veracity. It is challenging the conventional design in computer networking and dis- tributed computing, ranging from transmission, storage, processing, and system. This special section is an effort to promote research to address the big data challenges from the networking and distributed computing perspectives.
文摘The Computational Visual Media （CVM） Conference series is intended to provide a major international forum for exchanging novel research ideas and significant practical computational methods which either underpin or apply visual media. The primary rationale is to target cross-disciplinary research which amalgamates aspects of computer graphics, computer vision, machine learning, image processing, video processing, visualization and geometric computing. The main topics of interest to CVM include classification, composition, retrieval, synthesis, and understanding of visual media.
