Incremental addition to an augmented graph model

A non-transitory, computer-readable medium storing instructions that when executed by a computer system cause the computer system to perform operations comprising:

• accessing, at a computer system, an augmented graph model of (a) a set of transactions previously performed between respective pairs of initiator user accounts of a service and recipient user accounts of the service and (b) attribute values for a subset of the recipient user accounts,
• wherein the augmented graph model includes cluster nodes that:
• (a) have been inserted into attribute clusters identified within the augmented graph model and
• (b) are connected by weighted attribute edges to attributed nodes of the augmented graph model, wherein the attributed nodes are nodes that correspond to recipient user accounts having attribute values;
• receiving, at the computer system, additional information indicative of an additional transaction involving an additional recipient user account that is not represented in the augmented graph model with a node;
• modifying, by the computer system using the additional information, the augmented graph model by:
• representing the additional recipient user account as an additional node in the augmented graph model,
• if the additional node is within a threshold distance of one or more cluster nodes, connecting the additional node to a nearest cluster node with an additional weighted attribute edge;
• and
• if the additional node is outside of a threshold distance from any cluster nodes, inserting an additional cluster node into the augmented graph model and connecting the additional node to the additional cluster node with an additional weighted attribute edge;
• and
• grouping, with the computer system by applying one or more modularity algorithms to the modified augmented graph model, the user accounts represented in the modified augmented graph model into a plurality of groups.

A non-transitory, computer-readable medium storing instructions that when executed by a computer system cause the computer system to perform operations comprising:

• generating an augmented graph model of (a) a set of transactions previously performed between respective pairs of user accounts of a service and (b) attribute values for a subset of the user accounts, wherein the augmented graph model includes
• cluster nodes that have been inserted into attribute clusters identified within the augmented graph model;
• and
• indications of groupings of user accounts generated by applying one or more modularity algorithms to the augmented graph model, wherein weighted attribute edges of the augmented graph model are trained based on the groupings of user accounts;
• receiving, at the computer system, additional information indicative of an additional transaction involving an additional user account that is not represented in the augmented graph model with a node;
• modifying, by the computer system using the additional information, the augmented graph model by:
• representing the additional user account as an additional node in the augmented graph model,
• if the additional node is within a threshold distance of one or more cluster nodes, connecting the additional node to a nearest cluster node with an additional weighted attribute edge;
• and
• if the additional node is outside of a threshold distance from any cluster nodes, inserting an additional cluster node into the augmented graph model and connecting the additional node to the additional cluster node with an additional weighted attribute edge;
• and
• grouping, with the computer system by applying one or more modularity algorithms to the modified augmented graph model, the user accounts represented in the modified augmented graph model.