Abstract: An online system matches source and target entities using multiple queues. The online system performs clustering of target entities to generate a plurality of clusters based on vector distances between pairs of target entities. Each cluster comprises target entities that are close to other target entities within the cluster compared to target entities of remaining clusters. The online system optimizes an aggregate score across the plurality of entities using a plurality of queues. Each queue is associated with a source entity and includes one or more target entities. The online system identifies a cluster of target entities based on a distance between the source entities and entities of the cluster of target entities. The online system selects a subset of target entities from the identified cluster using a machine learning based model trained to determine a score between an input source entity and target entity.