Evaluating Feature Extraction Methods for Knowledge-based Biomedical Word Sense Disambiguation

@inproceedings{Henry2017EvaluatingFE,
  title={Evaluating Feature Extraction Methods for Knowledge-based Biomedical Word Sense Disambiguation},
  author={Sam Henry and Clint Cuffy and Bridget T. McInnes},
  booktitle={BioNLP},
  year={2017}
}
In this paper, we present an analysis of feature extraction methods via dimensionality reduction for the task of biomedical Word Sense Disambiguation (WSD). We modify the vector representations in the 2-MRD WSD algorithm, and evaluate four dimensionality reduction methods: Word Embeddings using Continuous Bag of Words and Skip Gram, Singular Value Decomposition (SVD), and Principal Component Analysis (PCA). We also evaluate the effects of vector size on the performance of each of these methods… CONTINUE READING

Similar Papers

Citations

Publications citing this paper.
SHOWING 1-2 OF 2 CITATIONS

References

Publications referenced by this paper.
SHOWING 1-10 OF 27 REFERENCES

Knowledge-Based Biomedical Word Sense Disambiguation with Neural Concept Embeddings

  • 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE)
  • 2016
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL