Paper Title
Content Recommendation Systems and Approaches Using Hybrid Filtering
Article Identifiers
: Authors
Keywords
Content Based Filtering, Collaborative Filtering, Hybrid Filtering.
Abstract
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.
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How To Cite (APA)
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
Issue
Volume 8 Issue 7, July-2023
Pages : b800-b804
Other Publication Details
Paper Reg. ID: IJNRD_201166
Published Paper Id: IJNRD2307190
Downloads: 000121991
Research Area: Computer Science & TechnologyÂ
Author Type: Indian Author
Country: HYDERABAD, TELANGANA, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2307190.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2307190
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