Movies and Books Recommendation System Based on Cosine similarity & K-Nearest Neighbour algorithm

Notification

Announcement!

ISJEM Invites papers for various areas like engineering, Management, Science & other multi discplinary subjects. Please submit your paper for review.

ISJEM assigns a digital object identifier (DOI) to each published paper, making it easier for the paper to be cited in various major databases like Google Scholar, ResearchGate, Academia.edu, etc…

ISJEM takes 24–48 hours to publish a research paper. Within 24 hours, the submitted paper will be reviewed and notified of its status, and it will be published once the processing fee is successfully received.

Movies and Books Recommendation System Based on Cosine similarity & K-Nearest Neighbour algorithm

Version
Download 45
File Size 469.99 KB
File Count 1
Create Date 13 June 2024
Last Updated 13 June 2024

Movies and Books Recommendation System Based on Cosine similarity & K-Nearest Neighbour algorithm

Authors:

Mohammad Hassaan, Mohammed Usman, Aman Sultan, Prof. Rita Kadam

Abstract:

A Recommendation System is a filtering program whose primary goal is to predict the “rating” or “preference” of a user towards a domain-specific item. In our case, this domain-specific item are movies and books. Hence the main focus of our recommendation system is to provide a total of five movies and books recommendations to users who searched for a movie or book that they like. This paper focuses on how recommendation system works in real world. The goal of recommender system is to generate meaningful recommendations to a collection of users for items or products that might interest them. The recommendation system is one of the major technologies for implementing personalization services.

Download