2026-05-20T04:57:39Zhttps://keep.lib.asu.edu/oai/requestoai:keep.lib.asu.edu:node-2005262025-06-04T23:12:05Zoai_pmh:alloai_pmh:repo_items200526
https://hdl.handle.net/2286/R.2.N.200526
http://rightsstatements.org/vocab/InC/1.0/
http://creativecommons.org/licenses/by-nc-sa/4.0
2025-05
19 pages
Patel, Samir
Osburn, Steven
Pokidaylo, Boris
Barrett, The Honors College
Computer Science and Engineering Program
School of Mathematical and Statistical Sciences
This paper outlines the development of an efficient glossary navigation system that uses
artificial intelligence to provide instant results through a dynamic search bar. The project uses
several tools, including Python, Hypertext Markup Language (HTML), Cascading Style Sheets
(CSS), JavaScript, and the Google Gemini API. Market research was conducted to ensure the
glossary stands out from other products, as few competitors integrate AI. Unlike the traditional
long, continuous pages of most competitors, this project displays only the words, showing
definitions only when needed. The integration of the Google Gemini-powered dynamic search
engine was successful, achieving the goal of eliminating manual navigation and simplifying the user experience with a streamlined, quick-access layout.
AI
Google Gemini
Glossary
Green Expectations: A Multi-Functional Search Engine for Enhanced Glossary Navigation