niitsuma/wordca

Distributed words representations using Correspondence Analysis

Word Correspondence Analysis(WCA)

Distributed words epresentations using Correspondence Analysis

more description in https://arxiv.org/abs/1605.05087

demo

>>> pip3 install delayedsparse numba 
>>> git clone https://github.com/niitsuma/wordca
>>> cd wordca
>>> bash  demo.sh

Usage

CORPUS=text8
MIN_COUNT=5
WINDOW=24
VECTOR_SIZE=8000
bash tailcut.sh $CORPUS $MIN_COUNT $WINDOW $VECTOR_SIZE

wor2vec format result

text8-5-24-1-tailcut-8000.F.vec is the result in word2vec format. The computed result can be downloaded from http://www.suri.cs.okayama-u.ac.jp/~niitsuma/wordca/text8-5-24-1-tailcut-8000.F.vec.bz2

correspondence analysis result

text8-5-24-1-tailcut-8000.dca.npz contains various information about correspondence analysis. Plz see save and load function in https://github.com/niitsuma/delayedsparse/blob/master/delayedsparse/ca.py

License

@2018 Hirotaka Niitsuma.

You can use these codes olny for self evaluation. Cannot use these codes for commercial and academical use.

• pantent pending
  • https://patentscope2.wipo.int/search/ja/detail.jsf?docId=JP225380312
  • Japan patent office:patent number 2017-007741 , 2018-126430

Author

Hirotaka Niitsuma.

@2018 Hirotaka Niitsuma.