We gratefully acknowledge support from
the Simons Foundation
and member institutions
Full-text links:


Current browse context:


Change to browse by:


References & Citations


(what is this?)
CiteULike logo BibSonomy logo Mendeley logo del.icio.us logo Digg logo Reddit logo ScienceWISE logo

Computer Science > Computation and Language

Title: Efficient Estimation of Word Representations in Vector Space

Abstract: We propose two novel model architectures for computing continuous vector representations of words from very large data sets. The quality of these representations is measured in a word similarity task, and the results are compared to the previously best performing techniques based on different types of neural networks. We observe large improvements in accuracy at much lower computational cost, i.e. it takes less than a day to learn high quality word vectors from a 1.6 billion words data set. Furthermore, we show that these vectors provide state-of-the-art performance on our test set for measuring syntactic and semantic word similarities.
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:1301.3781 [cs.CL]
  (or arXiv:1301.3781v3 [cs.CL] for this version)

Submission history

From: Tomas Mikolov [view email]
[v1] Wed, 16 Jan 2013 18:24:43 GMT (16kb)
[v2] Thu, 7 Mar 2013 21:40:37 GMT (48kb,D)
[v3] Sat, 7 Sep 2013 00:30:40 GMT (48kb,D)