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


Nattapong Sanchan, Naruepon Poojarern, and Chotirot Khampheng

    Abstract:

    Whereas the social tag clustering approach has been widely used in various recommender systems, recent work has rarely shown the utilization of the 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 application, utilizing a social tag clustering approach. Additionally, we also design the interface on mobile and conduct an experiment with three fundamental pipelines. The results indicated that the similarity measure affects the recommendation results. This contribution, the proposed framework using a social tag clustering approach, will add the novelty to the research communities and be 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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    Dowload bibtex entry: [BibTex] 
    @INPROCEEDINGS{2020_Sanchan,
  author={N. {Sanchan} and N. {Poojarern} and C. {Khampheng}},
  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},
  volume={},
  number={},
  pages={191-196},
  doi={10.1109/InCIT50588.2020.9310957}}
    Rich text bibliography entry (for copy & paste into a word processor):
    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.