Abstract: A system and method for social-aware clustering of user data replicas in a large-scale distributed computing system is disclosed. An exemplary system finds at least one user's connected users based on communications between the user and other users. The datacenters that contain the user replicas of the user's connected users are found. Connections and connection weights between the user and the user's connected users' datacenters are computed. The preferred datacenters for the user's current user data replica is computed based on the location of the connected datacenters and the weights of the connections. An optimization model minimizes the distance between the user's current datacenter and the user's preferred datacenter to reduce network traffic and central processing unit usage and determines the user's datacenter. The user's current datacenter is updated to the datacenter determined by running the optimization model.

Abstract: Provided are methods and systems for constructing a personal knowledge graph for a user based on data contained in existing e-mail messages of the user, and using the personal knowledge graph to provide the user with contextually-relevant content and/or contact suggestions while the user is composing an e-mail message. A personal knowledge graph is constructed based on relations/connections between users and content identified from data contained in e-mail messages sent and/or received by the user. Such relations include content-content relations, user-content relations, and user-(content)-user relations. When a user is composing an e-mail message, the system responsively processes, analyzes, and indexes composing e-mail message data. The composing e-mail message data is used to fetch relevant information from the user's personal knowledge graph and generate one or more content and/or contact suggestions for presentation to the user alongside an e-mail message composing view.