ML-based Telegram bot for real estate price prediction. (December 2020)

• Record Type: Journal Article
• Authors: Salem, Hamza; Mazzara, Manuel
• Is Part Of: Journal of physics. Volume 1694(2020)
• Publication Date: 2020-12
• Subjects: Machine Learning -- Real Estate -- web scrapping -- Telegram Bot -- Geolocation; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1694/1/012010
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Telegram chatbots are one of the main sections in Telegram applications that get more attention and provide huge business opportunities for companies nowadays. Also, Machine learning algorithms have been used in numerous fields and industries and one of the main growing markets is real estate. It is already helping real estate agents to respond more quickly to clients' questions and develop landing pages that fit customers' needs. However, one of the main time-consuming stages for a real estate agent is the process of answering questions about price per location and knowing which locations clients are interested in. In order to solve these problems, we have built a telegram chatbot to answer customers of any real estate agent with the price of a real estate property based on their current Geolocation. This bot can predict the price of a real estate property using room numbers, Geolocation, and surface area in square meters. These are the inputs for machine learning algorithms to give an approximate price. The bot can predict based on the source of the data-set, for example, we have collected our data from classified ads website for real estate in Amman, Jordan. We have used python and web scraping library for data extraction, cleaning, and transformation. As a result, by using Geolocation we have increased the model accuracy to 1.3X and our bot can be replicated in any markets based on the dataset. We believe our work can be taken to different markets and make real estate agent's job easy and more profitable by changing leads to potential customers thought answering their questions.