Knowledge discovery in ubiquitous environments is an emerging area of research at the intersection of the two major challenges of highly distributed and mobile systems and advanced knowledge discovery systems. It aims to provide a unifying framework for systematically investigating the mutual dependencies of otherwise quite unrelated technologies employed in building next-generation intelligent systems: machine learning, data mining, sensor networks, grids, peer-to-peer networks, data stream mining, activity recognition, Web 2.0, privacy, user modelling and others.
This state-of-the-art survey is the outcome of a large number of workshops, summer schools, tutorials and dissemination events organized by KDubiq (Knowledge Discovery in Ubiquitous Environments), a networking project funded by the European Commission to bring together researchers and practitioners of this emerging community. It provides in its first part a conceptual foundation for the new field of ubiquitous knowledge discovery - highlighting challenges and problems, and proposing future directions in the area of 'smart', 'adaptive', and 'intelligent' learning.
The second part of this volume contains selected approaches to ubiquitous knowledge discovery and treats specific aspects in detail. The contributions have been carefully selected to provide illustrations and in-depth discussions for some of the major findings of Part I.
| ISBN: | 9783642163913 |
| Publication date: | 19th October 2010 |
| Author: | Michael May, L Saitta |
| Publisher: | Springer an imprint of Springer Berlin Heidelberg |
| Format: | Paperback |
| Pagination: | 254 pages |
| Series: | Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence |
| Genres: |
Artificial intelligence Expert systems / knowledge-based systems Human–computer interaction Network hardware Algorithms and data structures Data mining Applied computing |
Knowledge discovery in ubiquitous environments is an emerging area of research at the intersection of the two major challenges of highly distributed and mobile systems and advanced knowledge discovery systems. It aims to provide a unifying framework for systematically investigating the mutual dependencies of otherwise quite unrelated technologies employed in building next-generation intelligent systems: machine learning, data mining, sensor networks, grids, peer-to-peer networks, data stream mining, activity recognition, Web 2.0, privacy, user modelling and others.
Ubiquitous Knowledge Discovery features in the following genres: Artificial intelligence, Expert systems / knowledge-based systems, Human–computer interaction, Network hardware, Algorithms and data structures, Data mining, Applied computing
Paperback. Not Available.
Ubiquitous Knowledge Discovery was written by Michael May, L Saitta and published by Springer an imprint of Springer Berlin Heidelberg
Ubiquitous Knowledge Discovery has 254 pages
Yes it is part of Lecture Notes in Computer Science. Lecture Notes in Artificial Intelligence series