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Evolving the Access Network
An in-depth piece that focuses on how companies can migrate their traditional networks to broadband—yet support new services without sacrificing the quality or profitability of either—this guide discusses which technology should be deployed and what the network impact of delivering such emerging services is.
Human-Computer Interaction. Theory, Design, Development and Practice
The 3-volume set LNCS 9731, 9732, and 9733 constitutes the refereed proceedings of the 18th International Conference on Human-Computer Interaction, HCII 2016, held in Toronto, ON, Canada, in July 2016. The total of 1287 papers and 186 posters presented at the HCII 2016 conferences and were carefully reviewed and selected from 4354 submissions. The papers thoroughly cover the entire field of Human-Computer Interaction, addressing major advances in knowledge and effective use of computers in a variety of application areas. The volumes constituting the full 27-volume set of the conference proceedings.
Virtual Teamwork
"This book, by Robert Ubell and his excellent team of collaborators, adds an important dimension to effective teaching and learning in online environments. It addresses how interaction and collaboration online can be effectively harnessed in virtual teams. It is an important contribution to the larger field of Internet-based education." —Frank Mayadas, Alfred P. Sloan Foundation How to create and manage highly successful teams online With the advent of the global economy and high-speed Internet, online collaboration is fast becoming the norm in education and industry. This book takes online collaboration to the next level, showing how you can bolster online learning and business performanc...
Reflections Termbook Class 01 Term 01
Reflections Termbook Class 01 Term 01
Knowledge Management
Provides comprehensive, in-depth coverage of all issues related to knowledge management, including conceptual, methodological, technical, and managerial issues. Presents the opportunities, future challenges, and emerging trends related to this subject.
Machine Learning and Knowledge Discovery in Databases
This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
Multilinear Subspace Learning
Due to advances in sensor, storage, and networking technologies, data is being generated on a daily basis at an ever-increasing pace in a wide range of applications, including cloud computing, mobile Internet, and medical imaging. This large multidimensional data requires more efficient dimensionality reduction schemes than the traditional techniqu
Adaptable and Adaptive Hypermedia Systems
Examines new hypermedia systems, discussing the benefits, impacts, and implications. This book covers the most current issues in the field, while providing insight into analytical and architectural aspects of the topic.
Tenth Scandinavian Conference on Artificial Intelligence
The Scandinavian Conference on Artificial Intelligence is one of the regional AI conferences in Europe. This title includes contributions that exemplify the diversity of research in artificial intelligence and confirm the achievement and magnitude of 25 years AI research in Scandinavia.
Rule Extraction from Support Vector Machines
Support vector machines (SVMs) are one of the most active research areas in machine learning. SVMs have shown good performance in a number of applications, including text and image classification. However, the learning capability of SVMs comes at a cost – an inherent inability to explain in a comprehensible form, the process by which a learning result was reached. Hence, the situation is similar to neural networks, where the apparent lack of an explanation capability has led to various approaches aiming at extracting symbolic rules from neural networks. For SVMs to gain a wider degree of acceptance in fields such as medical diagnosis and security sensitive areas, it is desirable to offer a...
