Content Recommendation Systems and Approaches Using Hybrid Filtering

Registration ID: IJNRD_201166

Published ID: IJNRD2307190

DOI: Click Here to Get

Hari Krishnan , Kusumalatha Karre , Sai Charan , C Rohit

Content Based Filtering, Collaborative Filtering, Hybrid Filtering.

Even though many people love watching movies, their choice of watching movies isn’t the same for every person, differs based on their various preferences like genre, actors, directors etc. When we take all this into account, it’s astoundingly difficult to generalize a movie and say that everyone would like it. To tackle this, we use Recommendation systems such as hybrid filtering. A movie recommendation system using hybrid filtering combines content-based and collaborative filtering methods to suggest movies to users. The content-based method uses movie features such as genre, plot, and actors to find similar movies, while the collaborative filtering method utilizes user behavior such as watching history, ratings, and user similarity to make recommendations. By combining these two methods, the system can provide more accurate and diverse movie suggestions to users.

Published Paper   E-Certificate

Hari Krishnan, Kusumalatha Karre, Sai Charan , & C Rohit (July-2023). Content Recommendation Systems and Approaches Using Hybrid Filtering. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(7), b800-b804. https://ijnrd.org/papers/IJNRD2307190.pdf

Volume 8 Issue 7, July-2023

Pages : b800-b804

Paper Reg. ID: IJNRD_201166

Published Paper Id: IJNRD2307190

Downloads: 000121983

Research Area: Computer Science & Technology 

Country: HYDERABAD, TELANGANA, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2307190.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2307190

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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