ChenglongChen / Tensorflow Dsmm
Licence: mit
Tensorflow implementations of various Deep Semantic Matching Models (DSMM).
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tensorflow-DSMM
Ongoing project for implementing various Deep Semantic Matching Models (DSMM). DSMM is widely used for:
- duplicate detection
- sentence similarity
- question answering
- search relevance
- ...
Quickstart
Data
This project is developed with regard to the data format provided in the 第三届魔镜杯大赛.
You can see /data/DATA.md
for the data format description and prepared data accordingly.
Your data should be placed in the data
directory. Current data
directory also holds a toy data.
If you want to run a quick demo, you can download data from the above competition link. Download is allowed after registration.
Demo
python src/main.py
Supported Models
Representation based methods
- DSSM style models
- DSSM: use FastText as encoder
- CDSSM: use TextCNN as encoder
- RDSSM: use TextRNN/TextBiRNN as encoder
Interaction based methods
- MatchPyramid style models
- MatchPyramid: use identity/cosine similarity/dot product as match matrix
- General MatchPyramid: use match matrices based on various embeddings and various match scores
- word embeddings
- original word embedding
- compressed word embedding
- contextual word embedding (use an encoder to encode contextual information)
- match score
- identity
- cosine similarity/dot product
- element product
- element concat
- word embeddings
- BCNN style models
- BCNN
- ABCNN1
- ABCNN2
- ABCNN3
- ESIM
- DecAtt (Decomposable Attention)
Building Blocks
Encoder layers
- FastText
- TimeDistributed Dense Projection
- TextCNN (Gated CNN and also Residual Gated CNN)
- TextRNN/TextBiRNN with GRU and LSTM cell
Attention layers
- mean/max/min pooling
- scalar-based and vector-based attention
- self and context attention
- multi-head attention
Acknowledgments
This project gets inspirations from the following projects:
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for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].