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The development of personalized wellness therapy recommender system using hybrid case-based reasoning

机译:基于混合案例推理的个性化健康治疗推荐系统的开发

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Rising costs in health care have encouraged individuals to become more aware of disease prevention. Therapy in the prevention of disease is very popular; this complementary and alternative medicine treatment is known as “wellness”. Wellness therapy is about balancing the harmony of body, mind and spirit, through physical beauty care, healthy diet, relaxation, environmental sensitivity and social contacts. However, in today's digital world, wellness information is not sufficient to meet the demands of users who tend to seek for wellness therapies suitable for themselves. Therefore, the wellness industry should provide effective solutions customised to an individual's needs and preferences. A study on enhancing the wellness recommendation services available on a wellness community portal was carried out to find the best technique(s) for matching users' wellness concerns with appropriate wellness therapy, and making reliable wellness recommendations based on individual preferences and wellness conditions. Hybrid case-based reasoning (HCBR) is the best approach for wellness therapy recommendation. HCBR uses three alternatives in suggesting solutions to users. The first alternative is to locate the same case in a case database to solve a user's current wellness concern. The second alternative is to match a user's wellness concerns with existing similar cases in a case database. The third alternative is to use a set of pre-determined standard rules in a rule-based reasoning (RBR) sub-system. The model proposed below will enhance users' knowledge and convenience in selecting suitable wellness therapy for their complementary and alternative medicine treatments.
机译:卫生保健成本上升鼓励个人更加了解疾病预防。治疗预防疾病是非常受欢迎的;这种互补和替代的药物治疗被称为“健康”。健康疗法是通过身体美容护理,健康饮食,放松,环境敏感和社会接触来平衡身体,心灵和精神的和谐。然而,在今天的数字世界中,健康信息不足以满足倾向于寻求适合自己的健康疗法的用户的需求。因此,健康行业应提供定制为个人需求和偏好的有效解决方案。进行了加强健康社区门户网站上可用的健康推荐服务的研究,以找到与适当的健康治疗相匹配用户的健康问题的最佳技术,并根据个体偏好和健康状况进行可靠的健康建议。杂交案例的推理(HCBR)是健康疗法推荐的最佳方法。 HCBR使用三种替代方案对用户的建议解决方案。第一替代方案是在案例数据库中定位相同的情况以解决用户的当前健康问题。第二种替代方案是将用户的健康问题与在案例数据库中的现有类似情况相匹配。第三种替代方案是在基于规则的推理(RBR)子系统中使用一组预定的标准规则。下面提出的模型将提高用户的知识和便利,为其互补和替代医学治疗选择合适的健康疗法。

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