  The recent emerging fields in data processing and manipulation has
facilitated the need for synthetic data generation. This is also valid for
mobility encounter dataset generation. Synthetic data generation might be
useful to run research-based simulations and also create mobility encounter
models. Our approach in this paper is to generate a larger dataset by using a
given dataset which includes the clusters of people. Based on the cluster
information, we created a framework. Using this framework, we can generate a
similar dataset that is statistically similar to the input dataset. We have
compared the statistical results of our approach with the real dataset and an
encounter mobility model generation technique in the literature. The results
showed that the created datasets have similar statistical structure with the
given dataset.
