%0 Conference Paper %1 anagnostopoulos2005prediction %A Anagnostopoulos, Christos %A Mpougiouris, Panagiotis %A Hadjiefthymiades, Stathes %B Proceedings of the 6th international conference on Mobile data management %C New York, NY, USA %D 2005 %I ACM %K CTII:WS1213 awareness context master prediction uni %P 137--141 %R 10.1145/1071246.1071266 %T Prediction intelligence in context-aware applications %U http://doi.acm.org/10.1145/1071246.1071266 %X Mobile applications are required to operate in ubiquitous environments of dynamic nature. Specifically, the availability of resources and services may vary significantly during a typical session of system operation. As a consequence, mobile applications need to be capable of adapting to these changes to ensure the best possible level of service to the user. Therefore, such adaptive applications may have pre-evaluated the appropriate knowledge of their environment to act efficiently. Such knowledge is not known a priori, so information prediction and proactivity should enhance and extend the functionality of such applications in order to be adaptable to the future changes of their underlying computational environment. In this paper, we discuss and evaluate such a context prediction algorithm. %@ 1-59593-041-8

@inproceedings{anagnostopoulos2005prediction, abstract = {Mobile applications are required to operate in ubiquitous environments of dynamic nature. Specifically, the availability of resources and services may vary significantly during a typical session of system operation. As a consequence, mobile applications need to be capable of adapting to these changes to ensure the best possible level of service to the user. Therefore, such adaptive applications may have pre-evaluated the appropriate knowledge of their environment to act efficiently. Such knowledge is not known a priori, so information prediction and proactivity should enhance and extend the functionality of such applications in order to be adaptable to the future changes of their underlying computational environment. In this paper, we discuss and evaluate such a context prediction algorithm.}, acmid = {1071266}, added-at = {2012-10-25T15:19:05.000+0200}, address = {New York, NY, USA}, author = {Anagnostopoulos, Christos and Mpougiouris, Panagiotis and Hadjiefthymiades, Stathes}, biburl = {https://www.bibsonomy.org/bibtex/24313bb6e13dc6d2f36de64461e3b1389/telekoma}, booktitle = {Proceedings of the 6th international conference on Mobile data management}, description = {Prediction intelligence in context-aware applications}, doi = {10.1145/1071246.1071266}, interhash = {df5318f4ee1aa4752e4568710aa5bb66}, intrahash = {4313bb6e13dc6d2f36de64461e3b1389}, isbn = {1-59593-041-8}, keywords = {CTII:WS1213 awareness context master prediction uni}, location = {Ayia Napa, Cyprus}, numpages = {5}, pages = {137--141}, publisher = {ACM}, series = {MDM '05}, timestamp = {2012-10-25T15:19:05.000+0200}, title = {Prediction intelligence in context-aware applications}, url = {http://doi.acm.org/10.1145/1071246.1071266}, year = 2005 }