A Framework for Mobile Personalized-Based Recommender System Using Social Tag Clustering Approach

Abstract

Whereas the social tag clustering approach has been widely used in various recommender systems, recent work has rarely shown the utilization of tag clustering in the development of mobile recommender systems. In this study, we explore the work in mobile recommendation systems and propose a framework for developing a personalized-based recommendation system for mobile applications, utilizing a social tag clustering approach. Additionally, we design the interface on mobile and conduct an experiment with three fundamental pipelines. The results indicate that the similarity measure affects the recommendation results. This contribution — the proposed framework using a social tag clustering approach — adds novelty to the research community and offers an alternative for developing future mobile recommendation systems.

Keywords: mobile recommender system, recommender system, tag clustering, social tag clustering, text clustering

References

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@inproceedings{2020_Sanchan,
  author    = {Sanchan, Nattapong and Poojarern, Naruepon and Khampheng, Chotirot},
  booktitle = {2020 - 5th International Conference on Information Technology (InCIT)},
  title     = {A Framework for Mobile Personalized-Based Recommender System Using Social Tag Clustering Approach},
  year      = {2020},
  pages     = {191--196},
  doi       = {10.1109/InCIT50588.2020.9310957}
}

N. Sanchan, N. Poojarern and C. Khampheng, “A Framework for Mobile Personalized-Based Recommender System Using Social Tag Clustering Approach,” 2020 – 5th International Conference on Information Technology (InCIT), Chonburi, Thailand, 2020, pp. 191–196, doi: 10.1109/InCIT50588.2020.9310957.