Normalization-based neighborhood model for cold start problem in recommendation system

Joint Authors

Zahid, Aafaq
Sharif, Nurfadhlina Mohd
Mustafa, Ayidah

Source

The International Arab Journal of Information Technology

Issue

Vol. 17, Issue 3 (31 May. 2020), pp.281-290, 10 p.

Publisher

Zarqa University Deanship of Scientific Research

Publication Date

2020-05-31

Country of Publication

Jordan

No. of Pages

10

Main Subjects

Information Technology and Computer Science

Abstract EN

Existing approaches for Recommendation Systems (RS) are mainly based on users’ past knowledge and the more popular techniques such as the neighborhood models focus on finding similar users in making recommendations.

The cold start problem is due to inaccurate recommendations given to new users because of lack of past data related to those users.

To deal with such cases where prior information on the new user is not available, this paper proposes a normalization technique to model user involvement for cold start problem or user likings based on the details of items used in the neighborhood models.

The proposed normalization technique was evaluated using two datasets namely MovieLens and GroupLens.

The results showed that the proposed technique is able to improve the accuracy of the neighborhood model, which in turn increases the accuracy of an RS.

American Psychological Association (APA)

Zahid, Aafaq& Sharif, Nurfadhlina Mohd& Mustafa, Ayidah. 2020. Normalization-based neighborhood model for cold start problem in recommendation system. The International Arab Journal of Information Technology،Vol. 17, no. 3, pp.281-290.
https://search.emarefa.net/detail/BIM-962325

Modern Language Association (MLA)

Zahid, Aafaq…[et al.]. Normalization-based neighborhood model for cold start problem in recommendation system. The International Arab Journal of Information Technology Vol. 17, no. 3 (May. 2020), pp.281-290.
https://search.emarefa.net/detail/BIM-962325

American Medical Association (AMA)

Zahid, Aafaq& Sharif, Nurfadhlina Mohd& Mustafa, Ayidah. Normalization-based neighborhood model for cold start problem in recommendation system. The International Arab Journal of Information Technology. 2020. Vol. 17, no. 3, pp.281-290.
https://search.emarefa.net/detail/BIM-962325

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 289-290

Record ID

BIM-962325