Con network

Con network. In our evaluation, we found that predicted seed sites are much more aggressive towards coverage and neighboring seeds than any seed algorithm that randomly chooses their predicted locations and neighbors. Interestingly, this prediction approach can also scale well with the number of data points available to perform seed selection for any given network model. Our results indicate that seeding can lead to fundamental efficiency gains for predictive clustering of queryed entities.