Context in problem solving: a survey

@article{Brézillon1999Survey, abstract = {Dealing with context seems to be a major challenge which the field of Artificial Intelligence (AI) will have to face in the next few years. The importance of the challenge is borne out by the various scientific events focusing on context which have been held since 1995. This does not mean that context has not been studied before—it has in such domains as Natural Language Processing—but it has yet to be studied in depth since previous research has only covered few aspects of the problem. We present in this paper a survey of the literature dealing directly and explicitly with context whatever the domain. This makes it possible for us to have a clear view of context in AI. One of the conclusions of this survey is to point out the existence of different types of context in areas such as the representation of knowledge in a computer system, the reasoning that the system carries out using the knowledge, and the interaction the system has with people.}, address = {New York, NY, USA}, author = {Br\'{e}zillon, Patrick }, citeulike-article-id = {1685718}, comment = {Surveys context defined as: "Context is what contrains a problem solving without internening in it explicitely" == Surveys context in domains related to AI * NLP, DBs \& ontologies, communication (human science), electronic documentation, vision. * Describes the PEPYS project which aims at using context as an indexing key for information retrieval == Context in AI * Surveys context in AI, covers also representation (as opposed to model in which also how to use it is included) of context by logic and rule-based. == The two sides of context * Engineering point of view: context known a priori, supposes that it may be modeled in a discrete representation and is static * Cognitive science: known a posteriori (during (inter-)action), dynamic, continuous and infinite The two views are not incompatible though. Nice conclusion (overview)}, doi = {http://dx.doi.org/10.1017/S0269888999141018}, issn = {0269-8889}, journal = {Knowl. Eng. Rev.}, keywords = {ai, context, d22, integration, l3s\_context\_workshop, survey}, month = {May}, number = {1}, pages = {47--80}, posted-at = {2007-09-22 14:53:42}, priority = {0}, publisher = {Cambridge University Press}, title = {Context in problem solving: a survey}, url = {http://dx.doi.org/10.1017/S0269888999141018}, volume = {14}, year = {1999} }

TY - JOUR ID - Brézillon1999Survey L3 - citeulike-article-id:1685718 TI - Context in problem solving: a survey JF - Knowl. Eng. Rev. VL - 14 IS - 1 SP - 47 EP - 80 AD - New York, NY, USA PB - Cambridge University Press SN - 0269-8889 N2 - Dealing with context seems to be a major challenge which the field of Artificial Intelligence (AI) will have to face in the next few years. The importance of the challenge is borne out by the various scientific events focusing on context which have been held since 1995. This does not mean that context has not been studied before—it has in such domains as Natural Language Processing—but it has yet to be studied in depth since previous research has only covered few aspects of the problem. We present in this paper a survey of the literature dealing directly and explicitly with context whatever the domain. This makes it possible for us to have a clear view of context in AI. One of the conclusions of this survey is to point out the existence of different types of context in areas such as the representation of knowledge in a computer system, the reasoning that the system carries out using the knowledge, and the interaction the system has with people. KW - ai KW - context KW - d22 KW - integration KW - l3s_context_workshop KW - survey N1 - Surveys context defined as: "Context is what contrains a problem solving without internening in it explicitely" == Surveys context in domains related to AI * NLP, DBs & ontologies, communication (human science), electronic documentation, vision. * Describes the PEPYS project which aims at using context as an indexing key for information retrieval == Context in AI * Surveys context in AI, covers also representation (as opposed to model in which also how to use it is included) of context by logic and rule-based. == The two sides of context * Engineering point of view: context known a priori, supposes that it may be modeled in a discrete representation and is static * Cognitive science: known a posteriori (during (inter-)action), dynamic, continuous and infinite The two views are not incompatible though. Nice conclusion (overview) AU - Brézillon, Patrick PY - 1999/05// UR - http://dx.doi.org/10.1017/S0269888999141018 ER -