Document Type

Poster

Publication Date

Spring 2024

Abstract

This project introduces a Retrieval-Augmented Film Recommendation System, developed as a Command Line Interface (CLI). It leverages advanced semantic search techniques, combined with retrieval-augmented generation, to deliver personalized movie recommendations. The system accesses extensive film metadata from two remote API sources, enriching the quality and accuracy of its suggestions. Tested across various movie preference profiles, the system adeptly adjusts its recommendations to suit individual tastes, showcasing its adaptability and the effectiveness of retrieval-augmented technology in streamlining user interactions with digital entertainment platforms.

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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