View source for Representations of Words and Phrases and their Compositionality

Representations of Words and Phrases and their Compositionality is a popular paper published by the Google team led by Tomas Mikolov  in 2013. It is known for its impact in the field of Natural Language Processing and the techniques described below are till in practice today.

= Presented by = 
*F. Jiang
*J. Hu
*Y. Zhang


= Introduction =
The Skip-gram model is a method of constructing a Word2Vec encoding using a neural network. Individual words are encoded 

[[File:skipmod.JPG|200px|thumb|left|alt text]]

= Skip Gram Model = 


= Hierarchical Softmax = 


= Negative Sampling = 


= Subsampling of Frequent Words = 


= Empirical Results =

=References=
[1] Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, Jeffrey Dean (2013). Distributed Representations of Words and Phrases and their Compositionality. arXiv:1310.4546.

[2] McCormick, C. (2017, January 11). Word2Vec Tutorial Part 2 - Negative Sampling. Retrieved from http://www.mccormickml.com