Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/59177
Title: Application of data mining into property industry to create an intelligent system
Authors: Young, Andrew Jing Lin
Keywords: DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications
Issue Date: 2014
Abstract: The property market is slow to innovate and adopt change resulting in inconvenience to all parties involved. This project explores the inefficiencies in the Singapore market and develops solution to help consumers make a more informed decision and improve the overall experience. Considerable amount of data comes from social media where Internet users are able to express themselves with freedom in the context of various topics. Choosing a property agent to sell a property and the knowledge of people living in an area can also affect the decision of consumers. In this project, we aim to gather the sentiments of users on the service of property agents and sentiments on the location of housing property and to analyse them, help consumers to gather information and make better decisions. Property sites are using traditional methods that require users to search by inputting text or browsing through the property list. Information on amenities near that particular property has to be found on other websites. In this project, the data is retrieved from the internet and together with the property listings, displayed to users on a map. From this map, users can search for nearby properties on a street/area with better visualization and user interaction saving the user time. With all the above mentioned, this project aims to build an intelligent system that displays to users properties on a map with nearby amenities and also sentiment analysis of property and property agents reviews to help users to make a better decision.
URI: http://hdl.handle.net/10356/59177
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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