%0 Journal Article %1 BettiniBrdiczkaEtAl10pmcj %A Bettini, Claudio %A Brdiczka, Oliver %A Henricksen, Karen %A Indulska, Jadwiga %A Nicklas, Daniela %A Ranganathan, Anand %A Riboni, Daniele %D 2010 %J Pervasive and Mobile Computing %K v1205 paper embedded ai adaptive knowledge processing ontology spatial location %N 2 %P 161-180 %R 10.1016/j.pmcj.2009.06.002 %T A Survey of Context Modelling and Reasoning Techniques %V 6 %X Development of context-aware applications is inherently complex. These applications adapt to changing context information: physical context, computational context, and user context/tasks. Context information is gathered from a variety of sources that differ in the quality of information they produce and that are often failure prone. The pervasive computing community increasingly understands that developing context-aware applications should be supported by adequate context information modelling and reasoning techniques. These techniques reduce the complexity of context-aware applications and improve their maintainability and evolvability. In this paper we discuss the requirements that context modelling and reasoning techniques should meet, including the modelling of a variety of context information types and their relationships, of high-level context abstractions describing real world situations using context information facts, of histories of context information, and of uncertainty of context information. This discussion is followed by a description and comparison of current context modelling and reasoning techniques and a lesson learned from this comparison.

@article{BettiniBrdiczkaEtAl10pmcj, abstract = {Development of context-aware applications is inherently complex. These applications adapt to changing context information: physical context, computational context, and user context/tasks. Context information is gathered from a variety of sources that differ in the quality of information they produce and that are often failure prone. The pervasive computing community increasingly understands that developing context-aware applications should be supported by adequate context information modelling and reasoning techniques. These techniques reduce the complexity of context-aware applications and improve their maintainability and evolvability. In this paper we discuss the requirements that context modelling and reasoning techniques should meet, including the modelling of a variety of context information types and their relationships, of high-level context abstractions describing real world situations using context information facts, of histories of context information, and of uncertainty of context information. This discussion is followed by a description and comparison of current context modelling and reasoning techniques and a lesson learned from this comparison.}, added-at = {2012-06-01T17:24:51.000+0200}, author = {Bettini, Claudio and Brdiczka, Oliver and Henricksen, Karen and Indulska, Jadwiga and Nicklas, Daniela and Ranganathan, Anand and Riboni, Daniele}, biburl = {https://www.bibsonomy.org/bibtex/27705bb7477fa5edc17193d092ee65584/flint63}, doi = {10.1016/j.pmcj.2009.06.002}, file = {Preprint:2010/BettiniBrdiczkaEtAl10pmcj.pdf:PDF}, groups = {public}, interhash = {1ca856ebab86e3de0d818bf9892af78b}, intrahash = {7705bb7477fa5edc17193d092ee65584}, issn = {1574-1192}, journal = {Pervasive and Mobile Computing}, keywords = {v1205 paper embedded ai adaptive knowledge processing ontology spatial location}, month = {#apr#}, number = 2, pages = {161-180}, timestamp = {2018-04-16T12:35:56.000+0200}, title = {A Survey of Context Modelling and Reasoning Techniques}, username = {flint63}, volume = 6, year = 2010 }