Developing a Contextually Personalized Hybrid Recommender System
Joint Authors
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-10-23
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Telecommunications Engineering
Abstract EN
It is hard to choose places to go from an endless number of options for some specific circumstances.
Recommender systems are supposed to help us deal with these issues and make decisions that are more appropriate.
The aim of this study is to recommend new venues to users according to their preferences.
For this purpose, a hybrid recommendation model is proposed to integrate user-based and item-based collaborative filtering, content-based filtering together with contextual information in order to get rid of the disadvantages of each approach.
Besides that, in which specific circumstances the user will like a specific venue is predicted for each user-venue pair.
Moreover, threshold values determining the user’s liking toward a venue are determined separately for each user.
Results are evaluated with both offline experiments (precision, recall, F-1 score) and a user study.
Both the experimental evaluation with a real-world dataset and a user study of the proposed system showed improvement upon the baseline approaches.
American Psychological Association (APA)
Bozanta, Aysun& Kutlu, Birgul. 2018. Developing a Contextually Personalized Hybrid Recommender System. Mobile Information Systems،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1204742
Modern Language Association (MLA)
Bozanta, Aysun& Kutlu, Birgul. Developing a Contextually Personalized Hybrid Recommender System. Mobile Information Systems No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1204742
American Medical Association (AMA)
Bozanta, Aysun& Kutlu, Birgul. Developing a Contextually Personalized Hybrid Recommender System. Mobile Information Systems. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1204742
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1204742