Semantic Models for Adaptive Interactive Systems
204 pages. 2013.
Tim Hussein, Heiko Paulheim, Stefan Lukosch, Jurgen Ziegler, Gaëlle Calvary
Hussein, T., Paulheim, H., Lukosch, S., Ziegler, J., Calvary, G. (Eds.) (Eds.)
HCI Series
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.