Portable devices are increasingly employed in a wide range of mobile guidance
applications. Typical examples are guides in urban areas, museum guides, and exhibition …

Internet has significantly influenced the tourism sector providing a great variety of services
and products online. However, the number of choices has increased so dramatically that is …

We present a machine learning algorithm for building classifiers that are comprised of a
small number of short rules. These are restricted disjunctive normal form models. An …

In this age of information overload, people use a variety of strategies to make choices about
what to buy, how to spend their leisure time, and even whom to date. Recommender …

The amount of touristic and travel information existing on the Internet is overwhelming.
Recommender systems are typically used to filter irrelevant information and to provide …

This study aims to identify antecedents and determinants affecting travelers' technological
acceptance of an app-based mobile tour guide (AMTG). Informativeness (IF) and …

Mobile tourist guides have attracted considerable research interest during the past decade,
resulting in numerous standalone and web-based mobile applications. Particular emphasis …

Increasingly manufacturers of smartphone devices are utilising a diverse range of sensors.
This innovation has enabled developers to accurately determine a user's current context. In …

This paper presents a context-aware mobile recommender system, codenamed Magitti.
Magitti is unique in that it infers user activity from context and patterns of user behavior and …

Context-aware systems are systems that have the ability to sense and adapt to the
environment. To operate in large-scale multi-stakeholder environments, systems often …