  Infomap clustering finds the community structures that minimize the expected
description length of a random walk trajectory; algorithms for infomap
clustering run fast in practice for large graphs. In this paper we leverage the
effectiveness of Infomap clustering combined with the multi-level graph drawing
paradigm. Experiments show that our new Infomap based multi-level algorithm
produces good visualization of large and complex networks, with significant
improvement in quality metrics.
