Reliable Hadith Recommender System

Mahtar, S. N. Mohamed; Khairudin, Nurkhairizan; Masrom, Suraya; Jaafar, S. N; Rahim, Siti Khatijah Nor Abdul; Azizan, Amizon

doi:10.1166/asl.2016.7082

Cited by 1 publication

(2 citation statements)

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“…As mentioned earlier, previous study [18,19,20,21] in recommender system indicate despite the fact that several BG recommender algorithms have been proposed, only a small number of projects are committed to the development of complete recommender system infrastructures and deal with chronic diseases such as GDM. In our study, the total of relevant result is 25 studies but we only obtained 20 studies that satisfied our inclusion criteria.…”

Section: Methods or Techniques In Bg Recommender System (Rq1)mentioning

confidence: 99%

“…As we reviewed the literature, we found several existing techniques for recommender system [18][19][20][21][22][23][24][25][26], but we do not know which one is the most appropriate for BG recommender system, particularly for patients with GDM. Therefore, in this study, we review research studies about BG recommender system that used several techniques to incorporate the BG recommender system and BG models for GDM.…”

Section: Introductionmentioning

confidence: 99%

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A mapping study on blood glucose recommender system for patients with gestational diabetes mellitus

Rosli¹,

Rosli²,

Nordin³

2019

Bulletin EEI

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Blood glucose (BG) prediction system can help gestational diabetes mellitus (GDM) patient to improve the BG control with managing their dietary intake based on healthy food. Many techniques have been developed to deal with blood glucose prediction, especially those for recommender system. In this study, we conduct a systematic mapping study to investigate recent research about BG prediction in recommender systems. This study describes an overview of research (2014-2018) about BG prediction techniques that has been used for BG recommender system. As results, 25 studies concerning BG prediction in recommender system were selected. We observed that although there is numerous studies published, only a few studies took serious discussion about techniques used to incorporate the BG algorithms. Our result highlighted that only one study discusses hybrid filtering technique in BG recommender system for GDM even though it has an ability to learn from experience and to improve prediction performance. We hope that this study will encourage researchers to consider not only machine learning and artificial intelligent techniques but also hybrid filtering technique for BG recommender system in the future research.

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Section: Methods or Techniques In Bg Recommender System (Rq1)mentioning

confidence: 99%