Honors Theses

Date of Award

Spring 5-8-2026

Document Type

Undergraduate Thesis

Department

Computer and Information Science

First Advisor

Jeffrey Lucas

Second Advisor

Bo Wang

Relational Format

Dissertation/Thesis

Abstract

Inspira is a cross-media recommendation platform designed to simplify how users discover and organize content across multiple domains. Instead of relying on separate platforms for movies, television shows, books, and music, Inspira provides a single interface where users can enter natural-language queries and receive recommendations from multiple categories at once. The system integrates external APIs, including TMDB, Spotify, and Google Books, to retrieve real-time content and present it in a unified format.

The platform supports user accounts, allowing individuals to save content to favorites, organize items into boards, and access a personalized dashboard. These features enable users not only to discover new content but also to manage and revisit their interests over time. The system is implemented as a full-stack web application using PHP for backend logic, MySQL for data storage, and standard web technologies for the frontend.

The development process involved designing the system architecture, integrating multiple APIs, and handling challenges related to data consistency and recommendation quality. Testing was conducted to ensure that all components functioned correctly and that the system provided a smooth user experience.

Overall, Inspira demonstrates how a unified approach to content discovery can reduce the complexity of navigating multiple platforms and create a more connected and personalized experience for users.

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