SMART STRUCTURE AND REAL ESTATE BUSINESS MANAGEMENT OF REAL ESTATE SECTOR USING REAL ESTATE BUSINESS MACHINE LEARNING MODEL
Abstract
vioft2nntf2t|tblJournal|Abstract_paper|0xf4ff28592c000000156c0d0001000800
The sales department follows the line-staff policy completely. The real estate business sector is covered with operations and sales are divided into autonomous components, but at the same time they have the same value and are equivalent to the work of the entire sector. Their only common goal is to get the buyer to buy this or that product. The fact that each component operates independently in the real estate business sector should not adversely affect the work, and each activity makes its own small contribution to the operations of the entire company. The distinctive features of any process are the presence of its direction and the organization of tasks to achieve the desired heights. In this paper, a smart real estate business machine learning model was proposed to structurized and manages the real estate real estate business. The purpose of this proposed model is to acquire the goods and services offered in the market by individuals or legal entities or to exchange them for other goods for mutual benefit. Interestingly, marketing-driven components are also driven by the real estate business sector. The structure of the proposed model is automated, but allows for many tasks to be performed at the same time. The main goal of the machine learning approach is to create a specific organization that aims to streamline sales and purchase processes, meet demand and make a profit.

Authors
M Raja
CMR Institute of Technology, India

Keywords
Autonomous Components, Business Machine Learning Model, Real Estate Real Estate
Yearly Full Views
JanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecember
000000000000
Published By :
ICTACT
Published In :
ICTACT Journal on Management Studies
( Volume: 8 , Issue: 2 , Pages: 1594-1598 )
Date of Publication :
May 2022
Page Views :
287
Full Text Views :
5

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.