Movie Recommendation System Using Convolution Neural Network

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Details

Web-based recommendation strategies, known as RS, have become increasingly relevant and widely utilized due to the vast amount of information available online. The demand for personalized and filtered systems continues to grow as a result. Recommendation systems serve as information filtering schemes that address the problem of information overload by extracting crucial insights from immense and continuously generated data. They predict user ratings or preferences for items, aiding in decision-making. This work explores various recommendation systems and algorithms applied specifically to movie recommendations.

Autorentext

La signora Jyoti Kumari lavora come professore assistente presso l'ITM di Gwalior. Ha pubblicato numerosi lavori di ricerca in conferenze e riviste rinomate. La sua area di ricerca è l'apprendimento automatico e la scienza dei dati. È tutor di studenti universitari in progetti di ricerca relativi all'apprendimento automatico.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09786206166894
    • Herausgeber LAP LAMBERT Academic Publishing
    • Anzahl Seiten 60
    • Genre Software
    • Sprache Englisch
    • Gewicht 107g
    • Untertitel Elevating Movie Recommendation through Advanced Clustering with Convolutional Neural Networks
    • Autor Jyoti Kumari , Sanjiv Sharma , Pradeep Yadav
    • Größe H220mm x B150mm x T4mm
    • Jahr 2023
    • EAN 9786206166894
    • Format Kartonierter Einband
    • ISBN 6206166899
    • Veröffentlichung 31.05.2023
    • Titel Movie Recommendation System Using Convolution Neural Network

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