Semantic Web technologies for context-aware museum tour guide applications

Traditionally, visitors to museums have been left having to choose between finding their way around exhibits on their own or taking a standardized group tour with a guide. In this paper, we describe a context-aware museum tour guide that adjusts its recommendations to the interests and contexts of individual visitors and enables them to selectively share their experience with others. The tour guide is built around an innovative semantic Web framework that minimizes the development and maintenance costs associated with the introduction of new exhibits, new visitor-oriented services and new sources of contextual information. In particular, it features a semantic Web rule reasoning engine that enables visitor-oriented services to identify relevant sources of contextual information and to enforce user-specified privacy preferences about what information they are willing to share with others (e.g. "only members of my group can see my current location", or "only my friends can see how I rate exhibits"). While still in prototype stage, the tour guide's target environment is the National Museum of Natural Science, one of Taiwan's largest museums with over 3 million visitors per year.