Real Estate Market Data Analysis and Prediction Based on Minor Advertisements Data and Locations’ Geo-codes

Abstract

Country’s economic status can derived from many complex and branched indicators, one of which is property prices estimation. Working on such indicator changed the state of literature from many perspectives and corners. Whilst the scarcity of such works imposes a need for it, and demonstrates an unutilized aspect of the economy that requires little resources to create some business and academic opportunities. In this work, efforts evolved to address the problem of estimating properties prices accurately, in specific apartment’s prices among The Amman City, The Capital of The Hashemite Kingdom of Jordan. Leading to shed the lights on employing data science different techniques namely data processing, analysis and predictive modeling for adopting and estimating the apartment’s prices based on advertisement data published through the web and its extracted location geocodes. In addition, the work evaluates the final analysis reported results based on selected evaluation measures, and compare them with other five similar works on such problem conducted in other countries. Trying to aim to enrich the literature with valuable insights gained using Machine Learning and Data Mining different predictive techniques mainly, and its related conditions, branches and requirements for other data processing and analysis techniques under the data science umbrella.