We present CrumbTrail, an algorithm to clean large and dense knowledge graphs. CrumbTrail removes cycles, out-of-domain nodes and non-essential nodes, i.e., those that can be safely removed without breaking the knowledge graph’s connectivity. It achieves this through a bottom-up topological pruning on the basis of a set of input concepts that, for instance, a user can select in order to identify a domain of interest. Our technique can be applied to both noisy hypernymy graphs – typically generated by ontology learning algorithms as intermediate representations – as well as crowdsourced resources like Wikipedia, in order to obtain clean, domainfocused concept hierarchies. CrumbTrail overcomes the time and space complexity limitations of current state-of-art algorithms.

- Interactive examples:

We provide 6 examples of the application of CrumbTrail to toy noisy graphs:

Once you open an example, click on a row of the table (on the right side of the screen) to visualize the corresponding steps of the algorithm.

- Source code:

- License

All the datasets and software are licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License: https://creativecommons.org/licenses/by/4.0/.