Authors :
Sushmita Roy.
Volume/Issue :
Volume 4 - 2019, Issue 2 - February
Google Scholar :
https://goo.gl/DF9R4u
Scribd :
https://goo.gl/pLejm1
Thomson Reuters ResearcherID :
https://goo.gl/KTXLC3
Abstract :
With the expeditious development of Information and Communications Technology and Web technologies, an enormous information is currently available and this results in a condition which in some cases is known as information overload. Due to these circumstances, it’s growing arduous for a person to discover and to access information for taking decisions expeditiously to arrive at an effective conclusion. To perorate this nut, there are filtering systems for information, such as the recommendation system or recommendation engine, considered here in this paper, that help a person in identifying significant, tectonic and possible services or products of interest based on the preferences given by him/her. Several approaches exist like – simple recommendation, popularity-based recommendation, collaborative filtering, content-based filtering demographic-based filtering and keyword or metadata-based filtering. This study has been undertaken to investigate the simple recommender-based approach. The efficiency of this proposed methodology is verified by experiments based on The Movies Dataset.
Keywords :
Recommendation System; Recommendation Engine; Movie Recommendation System.
With the expeditious development of Information and Communications Technology and Web technologies, an enormous information is currently available and this results in a condition which in some cases is known as information overload. Due to these circumstances, it’s growing arduous for a person to discover and to access information for taking decisions expeditiously to arrive at an effective conclusion. To perorate this nut, there are filtering systems for information, such as the recommendation system or recommendation engine, considered here in this paper, that help a person in identifying significant, tectonic and possible services or products of interest based on the preferences given by him/her. Several approaches exist like – simple recommendation, popularity-based recommendation, collaborative filtering, content-based filtering demographic-based filtering and keyword or metadata-based filtering. This study has been undertaken to investigate the simple recommender-based approach. The efficiency of this proposed methodology is verified by experiments based on The Movies Dataset.
Keywords :
Recommendation System; Recommendation Engine; Movie Recommendation System.
