Abstract
Purchasing of real estate property is a stressful and time-consuming activity, regardless of the individual in question is a buyer or seller. The act is also a major financial decision which can lead to numerous consequences if taken hastily. Therefore, it is encouraged that a person should properly invest their time and money in research relating to price demands, property type and location, etc. It can be a difficult task to assess what real estate property can be considered as the best property to buy. The key idea of the current research study is to create a set of standard rules, which should be embraced to make a smart decision of buying real estate property, based on web scraping technology and machine learning techniques.
Highlights
Any decision in relation to a property purchase or sales is a vital decision
That is not to say as it is impossible to do so as there are technological means available to the modern man that allow them to make the best decision. One such route is to take the assistance of web scraping technology
With changes in the current average property prices and the estimated average future growth rates, we create a set of standard rules for making decisions about buying a real estate property
Summary
Any decision in relation to a property purchase or sales is a vital decision. That is not to say as it is impossible to do so as there are technological means available to the modern man that allow them to make the best decision. One such route is to take the assistance of web scraping technology. This form of tech allows the user to find various online real state property advertisements from different web sources [2]. With the help of machine learning techniques such as decision tree C4.5 [3], in combination with the prior mentioned option, one can make a superior decision
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