Integrated baby-care recommender platform based on commonsense reasoning algorithm

To get baby care and medical-relative information via search engine of website is becoming a trend. However, nowadays, search engine for such information retrieve is almost "single-shot" searching process. Users are only allowed inputting target queries at beginning searching time which is inconsistent with reality human decision process in practice. This work proposed an integrated Baby Care (iBC) platform based on commonsense reasoning (CR) and cased based reasoning (CBR) algorithms. iBC enables users to retrieve baby-care information and share the experience and knowledge for baby care. Additionally, iBC provide user with babysitter matching mechanism. For both babysitter information and medical treatment recommendation, iBC can actually replicate the interactive decision making process in real world. Finally, to validate the feasibility and effectiveness of the proposed iBC platform, iBC platform is implemented and a demonstrated scenario is presented on iBC platform. There are 10 usual infant diseases that iBC can provide four treatments recommendation from traditional Chinese medical, modern medical and experienced treatment aspects. iBC is an integrated baby care knowledge platform that enables non-experience mothers to share baby-care experience and information that improve baby-care quality.