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Constructing a biodiversity terminological inventory.

Nhung T H Nguyen1, Axel J Soto1, Georgios Kontonatsios1

  • 1National Centre for Text Mining, School of Computer Science, University of Manchester, Manchester, United Kingdom.

Plos One
|April 18, 2017
PubMed
Summary
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This study introduces an automated method to build a biodiversity term inventory using text mining. This resource improves information discovery and search relevance by identifying species name variations.

Area of Science:

  • Biodiversity informatics
  • Computational biology
  • Text mining

Background:

  • The rapid growth of biodiversity literature necessitates efficient information retrieval.
  • Text mining offers automated solutions for knowledge discovery from large datasets.
  • Identifying concept variations (synonyms, term variants) is crucial for effective search.

Purpose of the Study:

  • To automatically construct a large-scale biodiversity term inventory using text mining.
  • To leverage distributional semantic techniques for identifying semantic similarity between species names.
  • To enhance semantic search and query expansion in biodiversity literature.

Main Methods:

  • Applied distributional semantic techniques to titles in the Biodiversity Heritage Library.

Related Experiment Videos

  • Computed semantic similarity between species names to build the term inventory.
  • Developed a visual search interface for query expansion using the inventory.

    • Main Results:

    • Successfully constructed a biodiversity term inventory with prevalent naming variations.
    • Demonstrated that distributional semantic models identify novel, semantically similar species names.
    • Showcased improved search relevance and document retrieval through automatic query expansion.

    Conclusions:

    • Automated term inventory construction is feasible and beneficial for biodiversity informatics.
    • Distributional semantics can aid in updating and enriching existing taxonomic resources.
    • The developed methods enhance search capabilities for biodiversity literature, aiding both users and developers.