Track 2: Taxonomy Applications – Monday 6 November
14:00 – 14:30
Machine learning algorithms can complement human intelligence with their ability to extract patterns from vast amounts of information rapidly. Algorithms that learn from reference text corpora can provide taxonomists with valuable insights: How complete is our taxonomy? Which areas need to be extended? Which are overrepresented? Hear how taxonomists can interact with a recommender system based on corpus learning. Blumauer discusses where the limitations are and why fully automated taxonomy or ontology creation will most probably never be possible. See how the resulting semantic knowledge graphs can be used for other purposes, like the extraction of “Shadow Concepts” or graph-based similarities between documents.
Presented by: Andreas Blumauer