International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 123 | Views: 204

M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 8 Issue 4, April 2019 | Rating: 6.8 / 10


Recommendation System Based on Behavioral Variability of User

Neethu Raj


Abstract: In real world web applications content recommendations are the most important thing to get better response to a user. Most of all users have less time span to search content in this busy environment. So they always seek improved result with minimum delay. Optimized content recommendation provides good content delivery. User actions and user feedback play a vital role in recommender systems. User feedback may be implicit user feedback or explicit user ratings on the recommended items. Appropriate user action interpretation is critical for a recommender system. This paper builds an online learning framework for personalized recommendation. The main contribution in this paper is an approach of interpreting users' actions for the online learning to achieve better item relevance estimation.


Keywords: Action interpretation, content optimization, personalization, recommender systems


Edition: Volume 8 Issue 4, April 2019,


Pages: 1080 - 1084


How to Download this Article?

Type Your Valid Email Address below to Receive the Article PDF Link


Verification Code will appear in 2 Seconds ... Wait

Top