Welcome to the InfoSci Platform
Reference Hub2
A New Contextual Influencer User Measure to Improve the Accuracy of Recommender System

A New Contextual Influencer User Measure to Improve the Accuracy of Recommender System

Maryam Jallouli, Sonia Lajmi, Ikram Amous
Copyright: © 2018 |Volume: 9 |Issue: 4 |Pages: 14
ISSN: 1947-3095|EISSN: 1947-3109|EISBN13: 9781522545316|DOI: 10.4018/IJSITA.2018100103
Cite Article Cite Article

MLA

Jallouli, Maryam, et al. "A New Contextual Influencer User Measure to Improve the Accuracy of Recommender System." IJSITA vol.9, no.4 2018: pp.38-51. http://doi.org/10.4018/IJSITA.2018100103

APA

Jallouli, M., Lajmi, S., & Amous, I. (2018). A New Contextual Influencer User Measure to Improve the Accuracy of Recommender System. International Journal of Strategic Information Technology and Applications (IJSITA), 9(4), 38-51. http://doi.org/10.4018/IJSITA.2018100103

Chicago

Jallouli, Maryam, Sonia Lajmi, and Ikram Amous. "A New Contextual Influencer User Measure to Improve the Accuracy of Recommender System," International Journal of Strategic Information Technology and Applications (IJSITA) 9, no.4: 38-51. http://doi.org/10.4018/IJSITA.2018100103

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

In the last decade, social-based recommender systems have become the best way to resolve a user's cold start problem. In fact, it enriches the user's model by adding additional information provided from his social network. Most of those approaches are based on a collaborative filtering and compute similarities between the users. The authors' preliminary objective in this work is to propose an innovative context aware metric between users (called contextual influencer user). These new similarities are called C-COS, C-PCC and C-MSD, where C refers to the category. The contextual influencer user model is integrated into a social based recommendation system. The category of the items is considered as the most pertinent context element. The authors' proposal is implemented and tested within the food dataset. The experimentation proved that the contextual influencer user measure achieves 0.873, 0.874, and 0.882 in terms of Mean Absolute Error (MAE) corresponding to C-cos, C-pcc and C-msd, respectively. The experimental results showed that their model outperforms several existing methods.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.