Mobile Application Curation Service Based On Big Data Platform

Popularization of smartphone allows many people to be able to share information, and easily get information they want. And then, app store of smartphone plays an important role to make users get information and make transactions they want easily. With the increase of the number of apps traded at the app store, it is difficult for users to find appropriate apps they want. Commonly, app store recommends apps users want through key words posted by users. But, this method has limits, and may not be satisfactory to users. This paper proposes a method where app store recommends apps to users by classifying apps used by users' friends by category and degree of satisfaction and recommending apps which are likely to be used. The experiment to test satisfaction of users showed that the method proposed in this paper increased the degree of satisfaction of users by over 21%.