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In this paper, we propose a new methodology based on directed graphs and the TextRank algorithm to automatically induce general-specific noun relations from web corpora frequency counts. Different asymmetric association measures are implemented to build the graphs upon which the TextRank algorithm is applied and produces an ordered list of nouns from the most general to the most specific. Experiments are conducted based on the WordNet noun hierarchy and assess 65.69% of correct word ordering.

Fully unsupervised graph-based discovery of general-specific noun relationships from web corpora frequency counts