A context model for knowledge-intensive case-based reasoning

Öztürk, Pınar; Aamodt, Agnar

doi:10.1006/ijhc.1997.0174

Cited by 40 publications

(13 citation statements)

References 31 publications

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“…Most notably the work by Strat [22], where context is applied to select the most suitable algorithm for recognition in computer vision, and byÖztürk and Aamodt [23] who utilised context to improve the quality and efficiency of Case-Based Reasoning.…”

Section: Context In Cognitionmentioning

confidence: 99%

Using Activity Theory to Model Context Awareness

Kofod-Petersen

Cassens

2006

Lecture Notes in Computer Science

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Abstract. One of the cornerstones of any intelligent entity is the ability to understand how occurrences in the surrounding world influence its own behaviour. Different states, or situations, in its environment should be taken into account when reasoning or acting. When dealing with different situations, context is the key element used to infer possible actions and information needs. The activities of the perceiving agent and other entities are arguably one of the most important features of a situation; this is equally true whether the agent is artificial or not. This work proposes the use of Activity Theory to first model context and further on populate the model for assessing situations in a pervasive computing environment. Through the socio-technical perspective given by Activity Theory, the knowledge intensive context model, utilised in our ambient intelligent system, is designed.

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Section: Context In Cognitionmentioning

confidence: 99%

Using Activity Theory to Model Context Awareness

Kofod-Petersen

Cassens

2006

Lecture Notes in Computer Science

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“…This is very much in line with the ideas proposed by Ekbia and Maguitman, where intelligence is action-oriented, and context can be use to bring order to diffuse situations. Oztürk and Aamodt [1998] demonstrate the use of context to improve the quality and efficiency of case-based reasoning. They also advocate an action-oriented view on reasoning and use of context by arguing that the essential aspects of context are the notion of relevance and focus.…”

Section: Behaviour and Context Are Jointly Recognisablementioning

confidence: 99%

Innovation and Creativity

Székely¹

2013

Gazdaság és Társadalom

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“…The very nature of CBR lends itself easily to reasoning about context and situation assessment. The use of context to guide the case-based reasoning process has been demonstrated in [7], where relevance and focus are regarded as the essential properties of context. The goal of an agent becomes part of the context used to focus the attention, and thereby to identify the knowledge needed to execute the actions associated with the goal.…”

Section: Background and Motivationmentioning

confidence: 99%

Contextualised Ambient Intelligence Through Case-Based Reasoning

Kofod-Petersen

Aamodt

2006

Lecture Notes in Computer Science

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Abstract. Ambient Intelligence is a research area that has gained a lot of attention in recent years. One of the most important issues for ambient intelligent systems is to perceive the environment and assess occurring situations, thus allowing systems to behave intelligently. As the ambient intelligence area has been largely technology driven, the abilities of systems to understand their surroundings have largely been ignored. This work demonstrates the first steps towards an ambient intelligent system, which is able to appreciate the environment and reason about occurring situations. This situation awareness is achieved through knowledge intensive case-based reasoning.

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A context model for knowledge-intensive case-based reasoning

Cited by 40 publications

References 31 publications

Using Activity Theory to Model Context Awareness

Using Activity Theory to Model Context Awareness

Innovation and Creativity

Contextualised Ambient Intelligence Through Case-Based Reasoning

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