App relationship calculation: An iterative process - Liu, Ming; Wu, Chong; Zhao, Xiang-Nan; Lin, Chin-Yew; Wang, Xiao-Long (International Conference on Data Engineering, 2016)
Today, plenty of apps are released to help users make the best use of their mobile phones. Facing the large amount of apps, app retrieval and app recommendation are extensively adopted to help users obtain their favorite apps. To acquire the high-quality retrieval or recommending results, it needs to obtain the accurate app relationship calculating results in advance. Unfortunately, recent methods are conducted mostly depending on user's log or app's contexts, which can only detect whether two apps are downloaded, installed meanwhile or provide similar functions or not. In fact, apps contain many deep relationships other than similarity, e.g., one app needs another app to cooperate to fulfill its work. Obviously, app's reviews contain user's viewpoint. They are useful to help dig deep relationship between apps. Therefore, to calculate relationship between apps via reviews, we propose an iterative process by combining review similarity calculation and app relationship calculation together.