In addition to SageMint, Eden is powered by SageRank, a dynamic interests ranking system. Inspired by Google’s PageRank, SageRank models the structure and evolution of the user-Circle interaction graph. Our heterogeneous dynamic graph embedding projects the social network, user activity, and Circle content to a high-dimensional space where similar users and Circles are close to each other in this vector space. Eventually, SageRank increases user engagement, Circle engagement, and boosts our effort to index the web.

SageRank starts its computation with selecting seed users who have an outstanding track record in indexing the web, and their indexing and purchasing behaviors of Circles will be taken as a signal to help us identify high quality Circles. At this stage, only the subgraph that contains the direct (one-hop) neighbors of the seed users and the seed users themselves will be embedded.

The authorship, indexing, or early investment of the high quality Circles helps us further identify even more credible and knowledgeable users. By random walks on the social network of users and Circles, SageRank iteratively updates its estimation of the credibility of quality of the users and Circles. Such estimation will be combined with language embedding on the Circles, social network embedding, and user behaviors (e.g. click streams, searches, and interests) to form as an input into a Hybrid Deep Recommender System (HDRS) that will optimizes the recommended Circles and Interests to users whose interest are most likely to be aligned with. HDRS helps Circles to get more traction and users discover the most valuable and interesting content, and the improved user experience can further boost the social and trading activity on our platform.

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