The content discovery platform for E-commerce: using social shopping and content-based in recommendation is the recommender approach that using social process together with the content-based technique to improve the model of recommendation. The model is designed to keep track of the customer direct behaviors as they engage with the artifacts, and also indirect behaviors for any social processes. Content discovery is used to suggest the products to their customer to help the customers find the right product for them to purchase based on customer activities and customer profile. Most people in this era using recommendation as part of their life to derive the decision involuntary. People always use their knowledge combine with some other reliable source of knowledge to make a decision on the artifacts that they are currently interested in. When people are buying the cosmetic or supplement, many time they try to find the information who has same tastes in these kind of artifacts from social world which is a big group of community that share the information with differences opinion.
Therefore, instead of using content based or collaborative filtering alone, we propose the combination of social processes with content based for more efficient in term of recommendation. With the point of people like to derive the information from external knowledge who shares the same taste might influence the people to make choices. For that reason, we try to bring the social intend to the model and make it better time to time with learning the behaviors and suggest the products or artifacts to the consumers from their taste.