Semantic Models for Adaptive Interactive Systems

Tim Hussein Heiko Paulheim Stefan Lukosch Jurgen Ziegler Gaëlle Calvary 1
1 LIG Laboratoire d'Informatique de Grenoble - IIHM
LIG - Laboratoire d'Informatique de Grenoble, Inria - Institut National de Recherche en Informatique et en Automatique
Abstract : Semantic technologies and, in particular, ontologies as formal and shareable representations of a domain play an increasingly important role in computer science, especially for the design, development and execution of interactive systems. Semantic models can serve a number of different purposes in this context. They can be used as functional core or user interface models in model-driven analysis, design, generation, and adaptation of user interfaces. Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways, e.g., by providing input assistance, intelligently clustering information, guiding collaborative interaction, or adapting the user interface according to the user's context. Especially in the latter case, ontologies can be applied for representing the various kinds of context information for context-aware and adaptive systems. In particular, they have promised to provide a technique for representing external physical context factors such as location, time or technical parameters, as well as "internal" context such as user interest profiles or interaction context in a consistent, generalized manner. Owing to these properties, semantic models can also contribute to bridging gaps, e.g., between user models, context-aware interfaces and model-driven UI generation. There is, therefore, a considerable potential for using semantic models as a basis for adaptive interactive systems. The range of potential adaptations is wide comprising, for example, context- and user-dependent recommendations, interactive assistance when performing application-specific tasks, adaptation of the application functionality, adaptation of the collaboration process, or adaptive retrieval support. Furthermore, a variety of reasoning and machine learning techniques exist, that can be employed to achieve adaptive system behavior. Last, but not least, the advent and rapid growth of Linked Open Data as a large-scale collection of semantic data has paved the way for a new breed of intelligent, knowledge-intensive applications. To explore that potential, we have established a workshop series called Semantic Models for Adaptive Interactive Systems (SEMAIS). The workshop had its debut at the ACM Intelligent User Interfaces conference in Hong Kong in 2010, and was followed by two subsequent editions in Palo Alto in 2011, and in Lisbon in 2012. At the workshop, we have seen cutting edge research spanning from the employment of semantic models in the development and generation of interactive systems to novel interaction paradigms and applications for semantic data. This book collects enhanced, revised, and updated versions of the best papers submitted to the three workshops editions, as well as additional original contributions. It provides insights into methodologies for designing adaptive systems based on semantic data, introduces models that can be used for building interactive systems, and showcases applications made possible by the use of semantic models.
Type de document :
Ouvrage (y compris édition critique et traduction)
Hussein, T., Paulheim, H., Lukosch, S., Ziegler, J., Calvary, G. (Eds.). Springer, pp.1-204, 2013
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https://hal.inria.fr/hal-00953366
Contributeur : Renaud Blanch <>
Soumis le : vendredi 28 février 2014 - 11:34:03
Dernière modification le : jeudi 11 janvier 2018 - 01:49:05

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  • HAL Id : hal-00953366, version 1

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Tim Hussein, Heiko Paulheim, Stefan Lukosch, Jurgen Ziegler, Gaëlle Calvary. Semantic Models for Adaptive Interactive Systems. Hussein, T., Paulheim, H., Lukosch, S., Ziegler, J., Calvary, G. (Eds.). Springer, pp.1-204, 2013. 〈hal-00953366〉

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