Optimization of cold start problem in recommendation systems: A review

Authors(2) :-Manali Patel, Pratik A. Barot

A major issue in collaborative filtering based recommendation systems is providing recommendations for a new user or to find a target user for a new item. This is referred to as a cold start problem in recommendation systems. This cold start problem is caused by lack of information about the said entity and it is very important issue to deal with. Many solutions have been suggested for a cold start problem. These solutions have not focused on the issue of personalization. Using one’s demographic attributes (age, gender, occupation) more accurate and interesting recommendations can be provided to the users. It makes recommender systems more personalized and leads to user satisfaction that is very important aspect for any e-commerce websites. Personality information can address cold start problem. We did literature survey and from our finding active learning can overcome cold start problem effectively.

Authors and Affiliations

Manali Patel
PG student, Department of Computer Engineering, Government Engineering College Gandhinagar, Gandhinagar, Gujarat, India
Pratik A. Barot
Assistant Professor, Department of Computer Engineering, Government Engineering College Gandhinagar, Gandhinagar, Gujarat, India

Recommendation systems, cold start, demographic attributes, Active learning

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Publication Details

Published in : Volume 3 | Issue 7 | September-October 2018
Date of Publication : 2018-10-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 369-374
Manuscript Number : CSEIT183776
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Manali Patel, Pratik A. Barot, "Optimization of cold start problem in recommendation systems: A review", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 7, pp.369-374, September-October-2018.
Journal URL : http://ijsrcseit.com/CSEIT183776

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