A Rental Advising System Based on Service Oriented Architecture

When considering a location to rent a living place, usually, there will be several factors that affect the final decision. Given various degree of importance to each factor, quite often, the result will be different. This paper describes a rental advising system that takes the importance degrees into consideration when ranking the living place, and provide tenants with suggested places that satisfy their requirements under these factors. We proposed a rental evaluation model to evaluate how each predefined factor affects ranking of living place and provide suggestions to the users. The system is created by mashing up several real Web services in order to provide the real data. Overall, the system provides users a new experience to search for a living place to rent.