Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Now-a-days people looking to buy a new house tend to be more cautious and careful with their budgets and market policies. The existing system involves computation of house prices without the crucial prediction about future market tendency and rate increase. Aim of this project was to develop a real estate web application using Microsoft ASP.NET and SQL 2008. The real estate system permit the functionality for users, allowing them to search for properties by features ,pricing or address. It also provides functionality for the seller vendor by authorizing them to log into the system and add and include new advertisements or delete and remove the existing ones. For this each user is provided with a login account and password. Along with this, when the user will quest for the property, initial property price and predicted property price will be displayed. By examining previous market trends and price sets, and also upcoming developments future prices will be predicted. For the price value prediction we will be applying classification algorithm. The functioning this project comprises a website which accepts customer’s specifications and then operates on the application of data mining. This application will aid customers to lend in an estate without approaching an agent or broker . It also reduces the hazards involved in the transaction.
Keywords:
Data mining, house price forecasting, prediction, linear regression, real estate
Cite Article:
"Customer Based Mapping of Real Estate Using Data Mining Techniques ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.4, Issue 4, page no.22 - 24, April-2019, Available :http://www.ijrti.org/papers/IJRTI1904006.pdf
Downloads:
000205169
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator