The act of using reason to derive a conclusion from certain premises using a given methodology. Location Based Services: Services that provide context-sensitive information based on the mobile user’s location.
Published in Chapter:
Semantic Web and E-Tourism
Danica Damljanovic (University of Sheffield, UK) and Vladan Devedžic (University of Belgrade, Serbia)
Copyright: © 2009
|Pages: 7
DOI: 10.4018/978-1-60566-026-4.ch544
Abstract
Offering tourist services on the Internet has become a great business over the past few years. Heung (2003) revealed that approximately 30% of travelers use the Internet for reservation or purchase of travel products or services. Classic sites of tourist agencies enable users to view and search for certain destinations and book and pay for vacation packages. At a higher level of sophistication are tourism Web portals, which integrate the offers of many tourist agencies and enable searching from one point on the Web. Still, when using this kind of systems one is forced to spend a lot of time analyzing Web content with destinations that match his/her wishes. This problem is identified by Hepp, Siorpaes and Bachlechner (2006) as the “needle in the haystack” problem. Applying artificial intelligence (AI) techniques in E-tourism could help resolve this problem by providing: 1. Data that are semantically enriched, structured, and thus represented in a machine readable form; 2. Easy integration of tourist sources from different applications; 3. Personalization of sites: the content can be created according to the user profile; 4. Improved system interactivity. As an example of using AI in e-tourism, we present Travel Guides—a prototype system that offers tourists complete information about numerous destinations. They can search destinations by using several criteria (e.g., accommodation type, food service, budget, activities during vacation, and user interests: sports, shopping, clubbing, art, museum, monuments, etc.). He/She can also read about the weather forecast and events in the destination. In a way, Travel Guides complements traditional information systems of tourist agencies. These systems require a lot of maintenance effort in order to keep the huge amount of data about tourist destinations up-to-date. Travel Guides is created to minimize the user’s input and his/her need to filter information. It shows how usage of semantically enriched data in a machine readable form can Increase interoperability in the area of tourism, Decrease maintenance efforts of tourist agents, and Offer tourists a better service. Nowadays, there are just a few e-tourism systems that use AI techniques. We briefly discuss them in the next section. In this article, we explain why it would be good to use such techniques and how Travel Guides does it. Specifically, using Semantic Web technologies in the area of tourism can improve already existing systems (which are mostly available online) that do not use Semantic Web techniques yet. Likewise, the Semantic Web approach can help decrease the maintenance efforts required for existing e-tourism systems and ease the process of searching for vacation packages. Travel Guides was initially developed as a large-scale expert system. Over time, it has evolved into a modern Semantic Web application.