Real estate recommender systems using case-base reasoning approach

• Main Author: Alrawhani, Ebrahim Mohammed Abdo
• Format: Thesis
• Language: English; English
• Published: 2014
• Subjects: QA Mathematics; QA76 Computer software
• Online Access: http://eprints.utem.edu.my/id/eprint/14846/1/Real%20estate%20Recommender%20Systems%20Using%20Case%20Base%20Reasoning%20Approach%2024pages.pdf; http://eprints.utem.edu.my/id/eprint/14846/2/Real%20estate%20recommender%20systems%20using%20case-base%20reasoning%20approach.pdf; http://eprints.utem.edu.my/id/eprint/14846/; https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=91016&query_desc=kw%2Cwrdl%3A%20Real%20estate%20recommender%20systems%20using%20case-base%20reasoning%20approach
• Institution: Universiti Teknikal Malaysia Melaka

The huge amount of data available on the Internet has lead to the development of online systems. This project proposes a Real Estate Recommender System using Case-Based Reasoning Approach which can help the customer to find a desired property. This proposed system uses a recommendation approach during search for property which assists the users to find an appropriate property and make decisions where they need the required knowledge to judge a particular property. Furthermore information available is very huge, so the recommender system assists the user to filter the available dataset according to user needs. Recommendation methods used for the search engine is Case-Based reasoning approach which can solve a new problem by retrieving the same problem that has been solved before and reuse the information that used to solve this new problem. Also the system uses collaborative filtering approach which filters the properties based on other user rating for properties; the system will do recommendation based on the top rated properties. In addition the system will recommend the user based on the most visited properties, where the system will count the number of visit to the database, and then based on the property with highest number of visit system will recommend the appropriate property to the users.