2013 TheExpressivePowerofWordEmbeddi

(Chen et al., 2013) ⇒ Yanqing Chen, Bryan Perozzi, Rami Al-Rfou, and Steven Skiena. (2013). “The Expressive Power of Word Embeddings.” In: CoRR, abs/1301.3226.

Subject Headings: Word Embedding System; SENNA Word Embedding System.

Notes

Cited By

Google Scholar: ~ 99 Citations.

Quotes

Abstract

We seek to better understand the difference in quality of the several publicly released embeddings. We propose several tasks that help to distinguish the characteristics of different embeddings. Our evaluation of sentiment polarity and synonym/antonym relations shows that embeddings are able to capture surprisingly nuanced semantics even in the absence of sentence structure. Moreover, benchmarking the embeddings shows great variance in quality and characteristics of the semantics captured by the tested embeddings. Finally, we show the impact of varying the number of dimensions and the resolution of each dimension on the effective useful features captured by the embedding space. Our contributions highlight the importance of embeddings for NLP tasks and the effect of their quality on the final results.

References

BibTeX

@article{2013_TheExpressivePowerofWordEmbeddi,
  author    = {Yanqing Chen and
               Bryan Perozzi and
               Rami Al-Rfou and
               Steven Skiena},
  title     = {The Expressive Power of Word Embeddings},
  journal   = {CoRR},
  volume    = {abs/1301.3226},
  year      = {2013},
  url       = {http://arxiv.org/abs/1301.3226},
  archivePrefix = {arXiv},
  eprint    = {1301.3226},
}

	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2013 TheExpressivePowerofWordEmbeddi	Steven Skiena Bryan Perozzi Rami Al-Rfou Yanqing Chen			The Expressive Power of Word Embeddings						2013