Integrated baby-care recommender platform based on hybrid commonsense reasoning and case-based reasoning algorithms

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