Attemptting to implement Shen, Yikang, et al. "Word Embedding Based Correlation Model for Question/Answer Matching." AAAI. 2017.
Training data: Yahoo! L4 - Yahoo! Answers Manner Questions and L6 - Yahoo! Answers Comprehensive Questions and Answers part1.
Python 3.6 & 2.7
Java 1.8.0
Tensorflow (Works on Python 3.6)
word2vec (Works on Python 2.7)
THUTag (Works on Linux)
Note: I will try to replace the heavy THUTag tool dependency with a light Python script later.
java -Xmx3G -jar tagsuggest.jar train.TrainWEC --input=../traindata/YahooPostL6-1-[time].dat --output=/mnt/hgfs/Data/thu-tag-workspace/trainWEC7 --config="dataType=KeywordPost;para=0.5;minwordfreq=10;mintagfreq=10;selfTrans=0.2;commonLimit=2"
Currently 48% by using DAG@1 evaluation method without using negative label.