Record Details

A New Approach for Movie Recommender System using K-means Clustering and PCA

Online Publishing @ NISCAIR

View Archive Info
 
 
Field Value
 
Authentication Code dc
 
Title Statement A New Approach for Movie Recommender System using K-means Clustering and PCA
 
Added Entry - Uncontrolled Name Yadav, Vikash ; ABES Engineering College, Ghaziabad
Shukla, Rati ; MNNIT Prayagraj, Allahabad
Tripathi, Aprna ; VIT Bhopal
Maurya, Anamika ; Harcourt Butler Technical University, Kanpur, India
 
Uncontrolled Index Term Principal Component Analysis (PCA); k-means clustering; Dunn index; Average similarity; Computational time, MovieLens
 
Summary, etc. Recommendation systems are refining mechanism to envisagethe ratings for itemsand users, to recommend likes mainly from the big data. Our proposed recommendationsystem gives a mechanism to users to classify with the same interest. This recommendersystem becomes core to recommend the e-commerce and various websites applications basedon similar likes. This central idea of our work is to develop movie recommender system withthe help of clustering using K-means clustering technique and data pre-processing usingPrincipal Component Analysis (PCA). In this proposed work, new recommendationtechnique has been presented using K-means clustering, PCA and sampling with the help ofMovieLens dataset. Our proposed method and its subsequent results have been discussed andcollation with other existing methods using evaluation metrics like Dunn Index, averagesimilarity and computational time has been also explained and prove that our technique isbest among other techniques. The results achieve from the MovieLens dataset is able to provehigh efficiency and accuracy of our proposed work. Our proposed method is able to achievethe MAE of .67, which is better than other methods.
 
Publication, Distribution, Etc. Journal of Scientific and Industrial Research (JSIR)
2021-02-11 17:54:36
 
Electronic Location and Access application/pdf
http://op.niscair.res.in/index.php/JSIR/article/view/40102
 
Data Source Entry Journal of Scientific and Industrial Research (JSIR); ##issue.vol## 80, ##issue.no## 02 (21)
 
Language Note en