Awesome

word2vec-get-started

Welcome

Fit language model tasks with word2vec and insuranceqa-corpus.

Install

scripts/compile.sh # verified on Ubuntu 16.04
source ./env.sh
word2vec # for verify

Train

cp localrc.sample localrc # modify keys
scripts/train.sh

Get similarities

Post training, a model file is generated in tmp, use distance to get similarities for words.

$ src/distance tmp/iqa.w2v.20170909113039.bin1.neg1.cbow0.win5.iter30.embed100.thr30
Enter word or sentence (EXIT to break): 家庭

Word: 家庭  Position in vocabulary: 83

                                              Word       Cosine distance
------------------------------------------------------------------------
                                            日托                0.648058
                                            住房                0.645767
                                            初创                0.631415
                                            宝石                0.621161
                                            家务                0.612938              

To compute all distances, use scripts/dist-analysis.sh MODEL_FILE

Principal component analysis(PCA)

• deps

Jupyter Notebook

Install

cd tools/word2vec_boostpy
python setup.py install
pip install -U numpy matplotlib scipy scikit-learn ipython jupyter 

Run

./scripts/pca.sh

Demo

open http://localhost:8888/notebooks/word2vec-get-started.ipynb

iqabot.v2

First, run ElasticSearch Service and Hanlp-api Service with elasticsearch-get-started.

cd iqabot.v2
cp config.sample.py config.py
python bot.py --query="为什么要获得医疗保险补充保险"

License

Apache 2.0

Trouble Shooting

1. compile error on Ubuntu install build essentials

sudo apt-get install build-essential