Housing Property Recommendation with Automated Requirement Prediction

  • Apoorva Pasbola, Rohil Saxena, Ms. R. Anita


With the growth of the IT industry in India people face the challenge of relocation ever so often. They are asked to switch to a new city and have a change in lifestyle. Our goal here is to aid this relocation process.This project is going to focus on supplementing the problem of recommending housing property for house buyers/renters. A key add on is the requirement prediction/estimation model, which uses the residents' information to estimate what will be the requirements for them. There are two models chained together to obtain the overall output. The first model will be used to predict the requirements that the house buyers will need. This coupled with their buying strength of the customers will be fed to another model to estimate the budget of the users. These two can be coupled with a recommendation system to reduce the workload on the end users who seek to buy property online. The training of both the models is done using Neural Network. Data for training these models will be gathered from online surveys and websites.

 Keywords—Artificial Neural Network, Artificial Intelligence, Machine Learning, Classification problem, Regression Problem, Real Estate, Web Scraping, Deep Learning.

How to Cite
Apoorva Pasbola, Rohil Saxena, Ms. R. Anita. (2020). Housing Property Recommendation with Automated Requirement Prediction. International Journal of Advanced Science and Technology, 29(06), 2479 - 2485. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/13681