Business Intelligence for Real Estate Advertising System

Abstract

We propose to build a real estate Advertising Using Business intelligence (REABI)-Real Estate Advertising Portal that allows users to post property for sale, Buy as well as search sort property and contact its owner online ,Payment gateway Page it gives location type of property, Also provide 24/7 service to all its users .Also in this we provide BI Panel which gives virtual tour of proposed property, Market survey analysis BI graph ,Quality assurance report, Every user having Profile which created at the time of Register ,and once registering is done then every time only login command is to use. This portal is Effecting on countries GDP rate. Because Real estate is 10%of total GDP

Introduction

Introduction:
The paper highlights the significance of targeted advertising in social networks using banner ads. These ads can be personalized based on user data and monitored in real-time for better engagement and effectiveness.

II. Research Survey:

A brief review of relevant studies and tools:

1. ACM: Focus on sponsored search advertising and keyword bidding.

2. Springer: Clustering methods for data pattern discovery.

3. IJIRMF: Big data architecture using Hadoop and Spark.

4. Web Advertising: Selection of data mining models for targeted ads.

5. IEEE: Importance of cloud-based advertising in platforms like Netflix and Amazon due to its cost-efficiency and scalability.

III. Proposed System (REABI):

A web-based advertising platform focusing on real estate listings. Major system modules include:

1. User Registration (Buyer/Seller)

2. Admin Panel – Manages ads and analytics.

3. Advertisement Posting/Search – Property listings and location-based search.

4. Data Validation & Login – Ensures valid user input and secure login.

5. Business Intelligence (BI) Panel – Manages media, user data, cities, and provides:

   • Banner/video/photo management

   • Advertising graphs

   • Virtual tours

   • Quality assurance reports

IV. Algorithm Used:

One-vs-All Classification Algorithm:
Used to categorize users into Buyer, Seller, or Agent using binary classifiers. The system generates separate models for each class and assigns class labels based on prediction scores.

Development Tools:

• Technologies: PHP, JavaScript, HTML

• Tools: UML, Selenium IDE, Google Web Dev

• Server: XAMPP

• OS: Windows/Linux

• RAM: 8GB

V. System Design:

1. Architecture Diagram: Outlines the system structure.

2. DFD (Data Flow Diagrams):

   • Level 0: Overview of major processes and data interactions.

   • Level 1/2/3: Detailed internal processes of each main component.

3. Use Case Diagram: Illustrates user interactions (ad posting, validation).

4. State Transition Diagram: (Not detailed, implied in system flow).

VI. UI Snapshots:

System interface views for desktop and Android platforms are mentioned but not shown in detail.

Additional Features:

• Media (photos, videos, banners, icons) management

• BI Panel for data insights

• Real-time quality assurance reports

Future Enhancements:

1. Property Price Comparison Charts – Help users make informed decisions.

2. Legal Advice Consultation – Legal verification of properties for safe transactions.

Conclusion

The Business Intelligence for Real Estate Advertising System is Portal and can easily be adopted by any of the Firm /company / Factory those are dealing with property selling; purchasing .there is huge Demand in real estate sector, and Its useful in todays life

References

[1] Akash Kumar Mohankumar, Nikit Begwani- “Query Rewriting in advertising”- 2106.03816-v1-2021-Aug ACM [2] Felix,tanza,Arthur- “clustering Refinement ”- 2020-Jan- [3] Springer- IJDSA [4] CHEN YANG, GEORGE G.Q. HUANG:Architecture for cloud collaboration A software defined perspective-2020- march -IEEE [5] Jerzy mauri szl-apczynski –„?web advertising in virtual communities „?-2019- Jan [6] AMR A. MUNSHI,YASSER ABDEL-RADY I. [7] MOHAMED-”Data Lake lambda architecture”-2018-July- IEEE [8] Charlie Bell,Yury Izrailevsky-“Cloud reliability”-2019- may -IEEE [9] Madhusudhan Reddy Sureddy,Prathyusha Yallamula- International Journal -Big data platform architecture - 2020-Aug-IJIRMF [10] Roger s. Pressman --”Software engineering ,Practitioner approach” , 6th edition [11] Roger s. Pressman -”Software engineering, Practitioner approach” , 6th edition [12] Roger s. Pressman -”Software engineering ,Practitioner approach” , 6th edition [13] Roger s. Pressman -”Software engineering ,Practitioner approach” , 6th edition [14] ibef.org(India Brand equity foundation) [15] Shang & Que -2018 “Precision Advertising system”

Copyright

Copyright © 2025 Raj Joshi, Abhishek Waghode, Prajwal Kumbhare, Dr. Amruta Surana. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.