Context-aware smartphone application category recommender system with modularized bayesian networks

Woo Hyun Rho, Sung Bae Cho

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

the number of applications available since the late 2010's, and the number of smartphone user sharply increasing. However, not all applications are not useful or helpful. In other words, to obtain satisfactory results in the search can be difficult means. Users to find what they want to search for a many times. To solve this problem, previous studies have proposed the use of recommender systems. Most of the system uses age, gender, preference based collaborative filtering. Collaborative filtering has the problem that data sparsity, cold-start or needs lots of users' personal data. In this paper, we propose a smartphone context-aware application category recommendation. We use Bayesian-network to inference context and recommend the category when inference context and we have set the probability of using category from collected data. We tested our proposed system with F1 measure, accuracy of inference context.

Original languageEnglish
Title of host publication2014 10th International Conference on Natural Computation, ICNC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages775-779
Number of pages5
ISBN (Electronic)9781479951505
DOIs
Publication statusPublished - 2014 Jan 1
Event2014 10th International Conference on Natural Computation, ICNC 2014 - Xiamen, China
Duration: 2014 Aug 192014 Aug 21

Publication series

Name2014 10th International Conference on Natural Computation, ICNC 2014

Other

Other2014 10th International Conference on Natural Computation, ICNC 2014
CountryChina
CityXiamen
Period14/8/1914/8/21

Fingerprint

Smartphones
Recommender systems
Bayesian networks
Collaborative filtering
Data privacy

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering

Cite this

Rho, W. H., & Cho, S. B. (2014). Context-aware smartphone application category recommender system with modularized bayesian networks. In 2014 10th International Conference on Natural Computation, ICNC 2014 (pp. 775-779). [6975935] (2014 10th International Conference on Natural Computation, ICNC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICNC.2014.6975935
Rho, Woo Hyun ; Cho, Sung Bae. / Context-aware smartphone application category recommender system with modularized bayesian networks. 2014 10th International Conference on Natural Computation, ICNC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 775-779 (2014 10th International Conference on Natural Computation, ICNC 2014).
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Rho, WH & Cho, SB 2014, Context-aware smartphone application category recommender system with modularized bayesian networks. in 2014 10th International Conference on Natural Computation, ICNC 2014., 6975935, 2014 10th International Conference on Natural Computation, ICNC 2014, Institute of Electrical and Electronics Engineers Inc., pp. 775-779, 2014 10th International Conference on Natural Computation, ICNC 2014, Xiamen, China, 14/8/19. https://doi.org/10.1109/ICNC.2014.6975935

Context-aware smartphone application category recommender system with modularized bayesian networks. / Rho, Woo Hyun; Cho, Sung Bae.

2014 10th International Conference on Natural Computation, ICNC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 775-779 6975935 (2014 10th International Conference on Natural Computation, ICNC 2014).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Rho WH, Cho SB. Context-aware smartphone application category recommender system with modularized bayesian networks. In 2014 10th International Conference on Natural Computation, ICNC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 775-779. 6975935. (2014 10th International Conference on Natural Computation, ICNC 2014). https://doi.org/10.1109/ICNC.2014.6975935