Temporal clustering

We are interested in finding similar patterns of check-in frequency over time dimension.

This leads us to temporal clustering. Check-ins for each venue based on time dimension can be represented as time series.

We tried two clustering methods: k-means, hierarchical clustering. The difference between them for the selected amount of data for a sample city was not that much huge.