Collaborative-based web recommender system for community-driven homestay programmes

• Main Author: Miraz, Mahadi Hasan
• Format: Thesis
• Language: English; English; English
• Published: 2017
• Subjects: TK5015.888 Web sites
• Online Access: https://etd.uum.edu.my/8357/1/s816976_01.pdf; https://etd.uum.edu.my/8357/2/s816976_02.pdf; https://etd.uum.edu.my/8357/3/s816976_references.docx; https://etd.uum.edu.my/8357/
• Institution: Universiti Utara Malaysia

A Homestay Programme (HP) is a kind of tourism initiative where local residents welcome tourists to stay and interact with them and experience the community’s daily activities and culture, including an option for lodging. The effects of HPs on the community are reflected in the development of the economy, social capital, infrastructure and environment. Hence, a HP promotes community-based tourism (CBT) and acts as a catalyst for rural community development. Most HPs are located in the rural areas, and thus, are directly linked to showcasing the various Malaysian cultures. Although homestay tourism is a growing industry in developing countries, there are some challenges faced in operating the Malaysian HPs since this CBT does not seem to be flourishing in a similar manner as the other tourism initiatives. All of these challenges have led to the main cause that is, lack of promotion and marketing due to the inability of homestay operators to utilize technology. Therefore, to overcome this, an enhanced Collaborative-Based Web Recommender (CBWR) system that meets certain criteria for an effective and efficient homestay service delivery is developed based on the user and item approach. This CBWR system acts as a database network that serves as an intermediary between users (visitors) and the service providers, who are the HP operator. Furthermore, this CBWR can also create a partnership between the homestay database and the homestay recommender website by capturing the users’ details and storing it, which is done by the profiler. Consequently, the profiler recommends several websites that suit to the user’s request. All these operations are carried out simultaneously to boost the functions of the CBWR system. Hence, this research contributes to the development of a specific unique web database and a CBWR system, which is adopted from collaborative algorithm. In addition, the CBWR system provides a supportive recommender algorithm which is carried out in a web enabling environment in real time. This enables users to find the available personalized website and unique HPs with their signature products and services.