In this work, we try to give a more precise meaning to the notion of "context" and to the knowledge associated with it, in order to build models representing a context able to adapt themselves to the user needs. We propose similarities as a tool to represent contexts. To do so, we consider a parametric fanfily of sunilarities and supply some methods for trying to "guess" the value of the parameter that best fits the context where the similarity shall be applied. We describe a general-purpose technique that derives a similarity starting from some sample information. Finally we give some hints on how to use our approach to develop adaptive user interfaces.
ARCELLI FONTANA, F., Formato, F. (2000). User Adaptive Models based on Similarity. In Proceedings of the 2000 ACM symposium on Applied computing (pp.501-504). New York : ACM Press [10.1145/335603.335931].
User Adaptive Models based on Similarity
ARCELLI FONTANA, FRANCESCA;
2000
Abstract
In this work, we try to give a more precise meaning to the notion of "context" and to the knowledge associated with it, in order to build models representing a context able to adapt themselves to the user needs. We propose similarities as a tool to represent contexts. To do so, we consider a parametric fanfily of sunilarities and supply some methods for trying to "guess" the value of the parameter that best fits the context where the similarity shall be applied. We describe a general-purpose technique that derives a similarity starting from some sample information. Finally we give some hints on how to use our approach to develop adaptive user interfaces.
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