Please use this identifier to cite or link to this item: https://dspace.rmutk.ac.th/jspui/handle/123456789/2112
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dc.contributor.authorสถาบันวิจัยและพัฒนา-
dc.date.accessioned2018-12-19T03:09:22Z-
dc.date.available2018-12-19T03:09:22Z-
dc.date.issued2017-
dc.identifier.urihttp://dspace.rmutk.ac.th/handle/123456789/2112-
dc.identifier.urihttps://www.tci-thaijo.org/index.php/rmutk/article/view/146979/108302
dc.description.abstractNowadays, the behavior of human life has been changed continuously and many people encounter the problems about health especially in fat reducing. This research presents how knowledge-based combined with rules can be used to develop the recommender system for weight loss activity to help the people for recommendations and produce a fat reducing plan. The question is how to automatically create a suitable plan and recommendation for weight loss activity, because the plan and recommendation should be compatible with individual people. Thus, the knowledge-based and rules in this research are proposed to solve the problems. There are three objectives of this research including 1) creating the ontology to represent the conceptual knowledge-based for activities of fat reducing and related information such as fat reducing activities, food, and disease, 2) creating the rules combined with proposed knowledge-based, and 3) developing the prototype system using proposed knowledge-based and rules to evaluate this approach. The accuracy is in the good level (average score = 0.73 (73%)). It is calculated using accuracy metrics by predictions with real users’ preferences and domain experts from real environment, 2 months.en_US
dc.description.sponsorshiplibrary.carit@mail.rmutk.ac.th
dc.language.isootheren_US
dc.publisherมหาวิทยาลัยเทคโนโลยีราชมงคลกรุงเทพen_US
dc.subjectWeight Loss Activityen_US
dc.subjectRecommender Systemen_US
dc.subjectOntological Knowledge-Baseden_US
dc.subjectRulesen_US
dc.titleระบบแนะนำกิจกรรมสำหรับการลดน้ำหนักโดยการประยุกต์ใช้ฐานความรู้แบบออนโทโลยีen_US
dc.typeOtheren_US
Appears in Collections:Vol 11 No 1 (2017)

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