Personalized e-Government Services: Tourism Recommender System Framework

This study proposes ontology-based personalized e-Gov tourism recommender system framework, which would enable tourism information seekers to locate the most interesting destinations and find the most preferable attractions and activities with less time and effort.

Abstract

Most governments around the globe use the internet and information technologies to deliver information and services for citizens and businesses. One of the main directions in the current e-government (e-Gov) development strategy is to provide better online services to citizens such that the required information can be located by citizens with less time and effort. Tourism is one of the main focused areas of e-Gov development strategy because it is one of the major profitable industries. Significant efforts have been devoted by governments to improve tourism services. However, the current e-Gov tourism services are limited to simple online presentation; intelligent e-Gov tourism services are highly desirable. Personalization techniques, particularly recommendation systems, are the most promising techniques to deliver personalized e-Gov (Pe-Gov) tourism services. This study proposes ontology-based personalized e-Gov tourism recommender system framework, which would enable tourism information seekers to locate the most interesting destinations and find the most preferable attractions and activities with less time and effort. The main components of the proposed framework and some outstanding features are presented along with a detailed description of a scenario.