A Content Boosted Collaborative Filtering Approach for Movie Recommendation Based on Local & Global Similarity and Missing Data Prediction

DOI10.1007/978-90-481-9794-1_22zbMath1198.68252OpenAlexW2130217170MaRDI QIDQ4932666

Hilal Karaman, Ferda Nur Alpaslan, Gözde Özbal

Publication date: 6 October 2010

Published in: Lecture Notes in Electrical Engineering (Search for Journal in Brave)

Full work available at URL: http://etd.lib.metu.edu.tr/upload/12610984/index.pdf

zbMATH Keywords

collaborative filteringrecommender systemsfloyd warshall algorithmpearsoncorrelation coefficient

Mathematics Subject Classification ID

Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35)

Cites Work

• A collaborative filtering framework based on both local user similarity and global user similarity

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