Social-PPM: Personal Experience Sharing and Recommendation

Abstract

The rise in popularity of various social network applications has brought the opportunities for Internet users to share and reuse a plethora of things like images, videos, datasets, ideas, interests, reviews etc. However, currently there is no effective way of sharing personal experiences such as the process of filing a personal income tax return or applying for a visa. We propose a social-aware process model and its implementation as a social network application that empowers users to create, to execute, and to share personal experiences within a social network at anytime and anywhere. As a social-aware process management system, it is important to have an effective recommender that predicts personal processes that a specific user may not be aware of and yet have the opportunity to enhance his/her life experiences. We adapt an existing collaborative filtering algorithm with emphasis on social context, the interaction history, and the type of interactions in processes for effective process recommendation. The assumption is that if two users have been copying and following same processes then it is likely that those two users have similar life goals, and this would be reflected in their future usage of the system as both of them will engage in similar processes.