The rapid development of communication technologies and web-based services generate a large amount of information. In recent years, recommender systems (RS) emerge as an effective mechanism to tackle the information overloading problems. By exploiting the cloud computing paradigm, RS discovers interesting new cultural items based on user preferences and interests. Recent investigations on RS reveal that employing social network data can yield enhanced personalised recommendations with better prediction accuracy. Since users tend to visit only conventional monuments, and many charming cultural items are hidden from them due to lack of awareness about the cultural sites. This article proposes a personalised recommendation model in the field of cultural heritage (CH) with the help of the cloud computing environment. The experimental results obtained demonstrate the improved performance of developed RS in the area of cultural heritage tourism services. Copyright © 2019 Inderscience Enterprises Ltd.