Student Research Symposium Program Portal

TUTORIAL

Please review the Student Research Symposium Tutorial for additional help:
https://docs.google.com/document/d/1JTvzK3C5hwM3WB9nXOUmvvcerrVHdPg4GpY9jRL1QH8/edit?usp=sharing

Submission information

Submission Number: 113

Submission ID: 8136

Submission UUID: 590e6f54-5ed5-4a46-992f-d09638932d30

Submission URI: /student-research/symposium/research-symposium-program-portal

Submission Update: /student-research/symposium/research-symposium-program-portal?token=vSGSH5DzYkule1SHos43RPKqX2cxjE7rUr4T4CYU7Jo

Created: Fri, 02/07/2025 - 10:14 PM

Completed: Fri, 02/07/2025 - 10:15 PM

Changed: Wed, 04/16/2025 - 12:53 PM

Remote IP address: 153.33.166.131

Submitted by: Anonymous

Language: English

Is draft: No

Webform: Research Symposium Program Portal WF

Submitted to: Student Research Symposium Program Portal

First Name

Last Name

Pronouns

FSU Student Email

Student Photo

Professional_Headshot.jpg29.58 KB

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One file only.
256 MB limit.
Allowed types: gif, jpg, png.

Major(s)

Student Bio

Poster Title

Abstract

APIs are crucial for modern application development, but discovering and accessing them efficiently remains difficult. This project introduces an automated API indexing and search platform designed to simplify that process. Using Python’s BeautifulSoup and Selenium libraries, the system scrapes public websites to extract key API information such as names, descriptions, and documentation links. The gathered data is organized into a searchable index, which powers a user-friendly web interface. Users can input keywords and receive quick, relevant API results—similar to using a traditional search engine. This approach helps developers find APIs faster and with greater accuracy. By combining static HTML parsing with dynamic web automation, the platform ensures broad and effective data collection. Early results show that this hybrid scraping method successfully builds a reliable API dataset. Planned improvements include adding ranking algorithms, collecting user feedback, and expanding data sources for wider coverage. This project demonstrates how web scraping and automation can address real-world problems in information retrieval, making API discovery more accessible and efficient for developers.

Research Mentor Name

Research Mentor's College (or High School)

Research Mentor's Department (or Subject)

Research Mentor's Email

Additional Research Mentor(s)

Co-presenter(s)

Keywords

Poster Session/Number

Work

Complete

Exploratory (the research question has been identified and design of approach is outlined)

Presentation Modality

Face to Face Poster session

Synchronous Online Presentation

Asynchronous Online Presentation

Poster PDF

Matthew_Brady_FSU_2025.pdf252.14 KB

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One file only.
256 MB limit.
Allowed types: pdf.

Poster Thumbnail

Please take a screenshot of your poster to be a thumbnail on your Symposium Program Profile.

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256 MB limit.
Allowed types: gif, jpg, png.

I will be printing my poster

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