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ExhibitorIQ: Intelligent Exhibitor Data Extraction and Event Outreach Platform
Subject area: Science,Engineering and Technology · Area of research: Market Data Mining & Lead Generation
Abstract
ExhibitorIQ is a full-stack, browser-based intelligent data extraction and event outreach platform that automates exhibitor data collection using multi-strategy web scraping, AI-powered catalog processing, email verification, and personalized campaign delivery. The system accepts trade show URLs, PDF catalogs, and uploaded spreadsheets, enabling multimodal data acquisition for a comprehensive exhibitor database. For URL-based inputs, the application employs a Playwright-driven headless browser stack with anti-bot evasion techniques including stealth fingerprinting, cookie persistence, proxy rotation, and Cloudflare bypass to extract exhibitor records from protected event websites. For PDF and image catalog inputs, the system leverages the Groq Vision API. Email validation is performed through format checking, disposable domain detection, MX record lookup, and optional Reoon API integration. The application is built using Python Flask, Pandas, BeautifulSoup4, openpyxl, and Playwright for a robust server-side architecture. By combining web scraping intelligence with AI document processing and automated campaign delivery, this system enhances event organizer productivity, data accuracy, and outreach efficiency in trade show management workflows.
Keywords
Exhibitor Data Extraction, Web Scraping, Anti-Bot Evasion, Playwright, Groq Vision AI, Email Verification, Event Management, Flask, Campaign Automation, PDF Processing, BeautifulSoup.
References
[1] S. Poria et al. 2019 S. Poria, D. Hazarika, N. Majumder, and R. Mihalcea, "Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances," IEEE Access, vol. 7, 2019.
[2] Erik Cambria et al. 2020 E. Cambria, D. Das, S. Bandyopadhyay, and A. Feraco, "A Practical Guide to Sentiment Analysis," Springer, 2020.
[3] Abhinav Dhall et al. 2021 A. Dhall, R. Goecke, S. Lucey, and T. Gedeon, "Collecting Large, Richly Annotated Data Databases from Web Sources," IEEE MultiMedia, vol. 19, 2021.
[4] Alex Radford et al. 2022 A. Radford et al., "Robust Document Understanding via Large-Scale Weak Supervision," OpenAI Technical Report, 2022.
[5] S. Parashakthi and R. Savithri 2022 S. Parashakthi and R. Savithri, "Intelligent Web Data Extraction for B2B Contact Management," Int. J. Computer Applications, 2022.
[6] Rohit Katkuri et al. 2023 R. Katkuri, A. Sharma, and P. Verma, "Anti-Bot Evasion Techniques in Modern Web Scraping Architectures," IEEE Conf. on Data Science, 2023.
[7] Björn W. Schuller et al. 2023 B. W. Schuller et al., "Multimodal Document Intelligence: State of the Art," IEEE Trans. Affective Computing, 2023.
[8] Groq, "Groq API Documentation," 2025. [Online]. Available: https://console.groq.com/docs
[9] Playwright, "Playwright for Python," Microsoft, 2025. [Online]. Available: https://playwright.dev/python
How to cite this paper
@article{1715669,
author = {Surya J, Dr. K. Ponmozhi},
title = {ExhibitorIQ: Intelligent Exhibitor Data Extraction and Event Outreach Platform},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {9},
pages = {2785-2791},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1715669.pdf},
abstract = {ExhibitorIQ is a full-stack, browser-based intelligent data extraction and event outreach platform that automates exhibitor data collection using multi-strategy web scraping, AI-powered catalog processing, email verification, and personalized campaign delivery. The system accepts trade show URLs, PDF catalogs, and uploaded spreadsheets, enabling multimodal data acquisition for a comprehensive exhibitor database. For URL-based inputs, the application employs a Playwright-driven headless browser stack with anti-bot evasion techniques including stealth fingerprinting, cookie persistence, proxy rotation, and Cloudflare bypass to extract exhibitor records from protected event websites. For PDF and image catalog inputs, the system leverages the Groq Vision API. Email validation is performed through format checking, disposable domain detection, MX record lookup, and optional Reoon API integration. The application is built using Python Flask, Pandas, BeautifulSoup4, openpyxl, and Playwright for a robust server-side architecture. By combining web scraping intelligence with AI document processing and automated campaign delivery, this system enhances event organizer productivity, data accuracy, and outreach efficiency in trade show management workflows.},
keywords = {Exhibitor Data Extraction, Web Scraping, Anti-Bot Evasion, Playwright, Groq Vision AI, Email Verification, Event Management, Flask, Campaign Automation, PDF Processing, BeautifulSoup.},
month = {March},
doi = {https://doi.org/10.64388/IREV9I9-1715669}
}