Authors: Logesh Ravi; Malathi Devarajan; Gwanggil Jeon; Oguz Bayat; V. Subramaniyaswamy
Addresses: Department of Computer Science and Engineering, Sri Ramachandra Faculty of Engineering and Technology, Sri Ramachandra Institute of Higher Education and Research, Chennai, Tamilnadu, India ' School of Computing, SASTRA Deemed University, Thanjavur, India ' Department of Embedded Systems Engineering, Incheon National University, Incheon, South Korea; School of Electronic Engineering, Xidian University, Xi'an, China ' Department of Electrical Engineering, Altinbas University, Istanbul, Turkey ' School of Computing, SASTRA Deemed University, Thanjavur, India
Abstract: 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.
Keywords: cloud computing; personalised recommender system; fuzzy-KNN; location-based social network; LBSN; cultural heritage.
International Journal of Web Based Communities, 2019 Vol.15 No.3, pp.271 - 288
Available online: 15 Aug 2019 *Full-text access for editors Access for subscribers Purchase this article Comment on this article