Random Vector Accumulator

  • RVA.py took 780 seconds to generate 5000 dimensional entity embeddings on 0.67% of the corpus when executed using cython, Word2Vec takes 200 seconds to generate 300 dimensional embeddings.
  • Storing only the position and value of non-zero components of the embeddings should be more memory efficient than storing individual components.
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