Large-Scale Semantic Indexing of Biomedical Publications

@inproceedings{Tsoumakas2013LargeScaleSI,
  title={Large-Scale Semantic Indexing of Biomedical Publications},
  author={Grigorios Tsoumakas and Manos Laliotis and Nikos Markantonatos and Ioannis P. Vlahavas},
  booktitle={BioASQ@CLEF},
  year={2013}
}
Automated annotation of scientific publications in real-world digital libraries requires dealing with challenges such as large number of concepts and training examples, multi-label training examples and hierarchical structure of concepts. BioASQ is a European project that contributes a large-scale biomedical publications corpus for working on these challenges. This paper documents the participation of our team to the large-scale biomedical semantic indexing task of BioASQ. 

Tables and Topics from this paper.

Citations

Publications citing this paper.
SHOWING 1-10 OF 24 CITATIONS

Results of the First BioASQ Workshop

VIEW 5 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

MeSH Now: automatic MeSH indexing at PubMed scale via learning to rank

  • J. Biomedical Semantics
  • 2017
VIEW 4 EXCERPTS
CITES METHODS
HIGHLY INFLUENCED

Fusion architectures for automatic subject indexing under concept drift

  • International Journal on Digital Libraries
  • 2018
VIEW 2 EXCERPTS
CITES BACKGROUND

References

Publications referenced by this paper.
SHOWING 1-9 OF 9 REFERENCES

Obtaining Bipartitions from Score Vectors for Multi-Label Classification

  • 2010 22nd IEEE International Conference on Tools with Artificial Intelligence
  • 2010
VIEW 1 EXCERPT

Mining Multi-label Data

  • Data Mining and Knowledge Discovery Handbook
  • 2009
VIEW 1 EXCERPT

A study of thresholding strategies for text categorization

Y. Yang
  • SIGIR ’01: Proceedings of the 24th annual international ACM SIGIR conference, New York, NY, USA, ACM
  • 2001
VIEW 1 EXCERPT