INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
This dissertation explores recommender systems,
focusing on addressing challenges related to data sparsity and
the cold-start problem. It uses the MovieLens dataset as a case
study and draws on deep learning techniques to tackle these
issues. The study delves into the foundations of deep learning
and adapts them to recommender systems, emphasizing the
significance of understanding data scarcity and new user or
item recommendations. It develops and evaluates custom
deep learning models optimized for MovieLens,
demonstrating their effectiveness in handling data sparsity
and the cold-start challenge. The research contributes to the
improvement of recommender systems by highlighting the
practical application of advanced deep learning in specific
datasets and domains, ultimately enhancing the quality of
recommendations in data-scarce scenarios and providing
insights for researchers, practitioners, and stakeholders.
Keywords:
Cite Article:
"A Comprehensive Study of Recommender Systems: Addressing Data Sparsity and the Cold-Start Predicament", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 9, page no.a831-a839, September-2023, Available :http://www.ijnrd.org/papers/IJNRD2309096.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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