Movie Recommendation System Using Convolution Neural Network - Kumari, Jyoti;Sharma, Sanjiv;Yadav, Pradeep
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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.…mehr

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Produktbeschreibung
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.
Autorenporträt
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.