Study and Comparative Analysis of Existing Recommender Systems

2019 ◽  
Vol 7 (1) ◽  
pp. 262-266
Author(s):  
Sanjay . ◽  
Yogesh Kumar ◽  
Rahul Rishi
Keyword(s):  
Comparative Analysis ◽  
Recommender Systems

scholarly journals A comparative analysis of recommender systems based on item aspect opinions extracted from user reviews

2018 ◽  
Vol 29 (2) ◽  
pp. 381-441 ◽  
Author(s):  
María Hernández-Rubio ◽  
Iván Cantador ◽  
Alejandro Bellogín
Keyword(s):  
Comparative Analysis ◽  
Recommender Systems ◽  
User Reviews

Improved Cluster-Minkowski Recommendation System (ICRS) for Collaborative Filtering

2019 ◽  
Vol 16 (9) ◽  
pp. 3892-3896
Author(s):  
Bhavana ◽  
Neeraj Raheja
Keyword(s):  
Comparative Analysis ◽  
Collaborative Filtering ◽  
Recommender Systems ◽  
Recommendation System ◽  
Intelligent System ◽  
User Preferences ◽  
User Profiles ◽  
Content Filtering ◽  
History Of ◽  
Clustering Approach

Recommendation systems are intelligent system which provides suggestion according to user adaptability. Recommender systems i.e., collaborative filtering and content filtering works on the basis of user profiles, extensive history of user preferences and item descriptions. This paper proposes an improved recommendation system based on clustering approach. The comparative analysis shows that the proposed system provides better results in terms of RMSE as compared to other already existing methods.

1207: Failed Pyeloplasty in Children: Comparative Analysis of Retrograde Endopyelotomy VS. Re-do Pyeloplasty

2007 ◽  
Vol 177 (4S) ◽  
pp. 398-398
Author(s):  
Luis H. Braga ◽  
Joao L. Pippi Salle ◽  
Sumit Dave ◽  
Sean Skeldon ◽  
Armando J. Lorenzo ◽  
...  
Keyword(s):  
Comparative Analysis
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