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Recommendation System
An information retrieval system that recommends anime and manga using TF-IDF similarity, spell correction, and user feedback loops.
Built as an academic project to apply information retrieval theory to a real dataset: recommends anime and manga using TF-IDF cosine similarity on synopses, genres, and user preferences.
Features document ranking, query spell correction, and a feedback loop that refines recommendations based on user interactions and viewing history.
Implemented with Flask and Python, serving as a hands-on exploration of search algorithms, inverted indices, and relevance scoring.
Tech Stack
FlaskPythonHTML/CSSIR Similarity Algorithm