A Short Survey on Taxonomy Learning from Text Corpora: Issues, Resources and Recent Advances

نویسندگان

  • Chengyu Wang
  • Xiaofeng He
  • Aoying Zhou
چکیده

A taxonomy is a semantic hierarchy, consisting of concepts linked by is-a relations. While a large number of taxonomies have been constructed from human-compiled resources (e.g., Wikipedia), learning taxonomies from text corpora has received a growing interest and is essential for longtailed and domain-specific knowledge acquisition. In this paper, we overview recent advances on taxonomy construction from free texts, reorganizing relevant subtasks into a complete framework. We also overview resources for evaluation and discuss challenges for future research.

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تاریخ انتشار 2017