Using Social Tags and User Rating Patterns for Collaborative Filtering

Iljoo Kim and Vipul Gupta
Additional contact information
Iljoo Kim: Decision and System Sciences Department, Haub School of Business, Saint Joseph's University, Philadelphia, PA, USA
Vipul Gupta: Decision and System Sciences Department, Haub School of Business, Saint Joseph's University, Philadelphia, PA, USA

International Journal of Information Systems and Social Change (IJISSC), 2017, vol. 8, issue 2, 25-49

Abstract: The overwhelming supply of online information on the Web makes finding better ways to separate important information from the noisy data ever more important. Recommender systems may help users deal with the information overloading issue, yet their performance appears to have stalled in currently available approaches. In this study, the authors propose and examine a novel user profiling approach that uses collaborative tagging information to enhance recommendation performance. They evaluate the proposed hybrid approach, illustrated in the context of movie recommendation. The authors also empirically evaluate various existing recommendation approaches (in comparison with the newly proposed approach) using sensitivity analyses to investigate the potential use of varied user rating or tagging patterns to improve recommendations accuracy. The results don't just indicate the effective and competitive performance of the suggested approach, but they also suggest important implications and directions for further research, including the potential associated with applying multiple recommendation approaches within a single system based on the different rating or tagging patterns of the user.

Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJISSC.2017040102 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jissc0:v:8:y:2017:i:2:p:25-49

Access Statistics for this article

International Journal of Information Systems and Social Change (IJISSC) is currently edited by John Wang

More articles in International Journal of Information Systems and Social Change (IJISSC) from IGI Global
Bibliographic data for series maintained by Journal Editor ().