  We present an interactive Web platform that, given a directed graph, allows
identifying the most relevant nodes related to a given query node. Besides
well-established algorithms such as PageRank and Personalized PageRank, the
demo includes Cyclerank, a novel algorithm that addresses some of their
limitations by leveraging cyclic paths to compute personalized relevance
scores. Our demo design enables two use cases: (a) algorithm comparison,
comparing the results obtained with different algorithms, and (b) dataset
comparison, for exploring and gaining insights into a dataset and comparing it
with others. We provide 50 pre-loaded datasets from Wikipedia, Twitter, and
Amazon and seven algorithms. Users can upload new datasets, and new algorithms
can be easily added. By showcasing efficient algorithms to compute relevance
scores in directed graphs, our tool helps to uncover hidden relationships
within the data, which makes of it a valuable addition to the repertoire of
graph analysis algorithms.
