Author Login IJIRT Partner Network (IPN) Login

UNVEILING TRENDS: DATA CLUSTERING ANALYSIS OF NETFLIX TV SHOWS AND MOVIES THROUGH EDA

  • Unique Paper ID: 167501
  • Volume: 11
  • Issue: 3
  • PageNo: 1509-1513
  • Abstract:
  • This paper explores unsupervised clustering analysis of Netflix's extensive collection of movies and TV shows using advanced techniques such as K-means, Agglomerative Clustering, and Affinity Propagation. Leveraging technologies like Word2Vec for word embedding, the study focuses on optimizing clustering models through meticulous data preprocessing, text cleaning, and hyper-parameter tuning. Key criteria such as Silhouette Score, Elbow Method, and Dendrogram are employed to determine the optimal number of clusters. Insights from exploratory data analysis reveal Netflix's strategic shift towards emphasizing TV content over movies globally. The findings contribute to understanding content preferences across different regions and showcase the platform's effective use of machine learning and AI for personalized recommendations.
Download article email to a friend

Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 3
  • PageNo: 1509-1513

UNVEILING TRENDS: DATA CLUSTERING ANALYSIS OF NETFLIX TV SHOWS AND MOVIES THROUGH EDA

Related Articles

Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now

Latest Publication

Archive

View More

Recent Conferences

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024 Last Date: 15th March 2024

Submit inquiry