MatchPyramid-for-semantic-matching

A simple Keras implementation of MatchPyramid model for semantic matching.
Please refer paper：Text Matching as Image Recognition

Quick Glance

1. Input Data Format

• Train/Valid set:

label	|q1	|q2
1	|Q2119	|D18821
0	|Q2119	|D18822

• Test set:

q1	|q2
Q2241	|D19682
Q2241	|D19684

• Preprocessed Corpus:

qid	|words
D9980	|47 0 1 2 3 4 5 6 7 8 9 10
D5796	|21 40 41 42 43 44 14 45

• Word Embedding:

word	|embedding (50-dimension)
28137	|-0.54645991 2.28509140 ... -0.34052843 -2.01874685
8417	|-9.01635551 -3.80108356 ... 1.86873138 2.14706421

• Word Dictionary:

word	|wid
preparing	|0
to	|1
rebuild	|2

2. Train the model

$ python match_pyramid.py

3. Loss and Accuracy
   

	Best Valid loss	Best Valid accuracy
WikiQA	0.3973	0.8786
QouraQP	0.4525	0.7797

Requirements

• Python 3.5
• TensorFlow 1.8.0
• Keras 2.1.6