Recent developments in internet technologies have created a massive demand for online services with the rapidly growing users. Travel recommender systems have been embraced by many researchers due to recent developments and significant requirements in the e-tourism domain. Generating personalised recommendations with minimal interactions is a key challenge and predicting personalised list of locations with the available ratings alone cannot achieve effective recommendations. To address this issue, we develop an intelligent real-time user-specific travel recommender system (IRTUSTRS) through incorporating users' social network profile and current location by exploiting global positioning system (GPS) data for travel recommendation generation. The proposed IRTUSTRS approach helps end users through enhanced travel recommendations with improved accuracy. The experimental evaluation portrays the improved performance of IRTUSTRS over baseline approaches. The presented work helps to understand the performance of recommender systems by utilising online social network profile of users with the current location through the GPS data. © 2018 Inderscience Enterprises Ltd.