本项目实现了语义匹配的几个模型，分别为：
DSSM
Learning Deep Structured Semantic Models for Web Search using Clickthrough Data
ESIM
Enhanced LSTM for Natural Language Inference
Pair-CNN
Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks
ABCNN
ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs
BIMPM
bilateral multi-perspective matching for natural language sentences
论文及papers在文件夹中
文本匹配的相关模型DSSM,ESIM,ABCNN,BIMPM等，数据集为LCQMC官方数据.zip
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2023-10-19
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文本匹配的相关模型DSSM,ESIM,ABCNN,BIMPM等，数据集为LCQMC官方数据.zip （48个子文件） 
text_matching-master dssm 
dssm_model.py 4KB
dssm相关说明.txt 968B bimpm match_utils.py 26KB layer_utils.py 12KB BiMPM.py 13KB esim infer.py 3KB esim_model.py 6KB train.py 6KB __pycache__ esim_model.cpython-35.pyc 5KB abcnn abcnn_mdoel.py 16KB abcnn_model_pre.py 12KB infer.py 2KB train.py 6KB __pycache__ abcnn_mdoel.cpython-35.pyc 8KB lstm bi_lstm_attention.py 6KB infer.py 3KB bi_lstm.py 4KB train.py 6KB __pycache__ bi_lstm.cpython-35.pyc 4KB save_model esim checkpoint 199B vocab.pickle 67KB abcnn checkpoint 201B vocab.pickle 66KB lstm checkpoint 199B vocab.pickle 66KB paircnn checkpoint 205B vocab.pickle 67KB papers 
Bilateral Multi-Perspective Matching for Natural Language Sentences.pdf 359KB Enhanced LSTM for Natural Language Inference.pdf 985KB Attention-Based Convolutional Neural Network for Modeling Sentence Pairs.pdf 572KB MultiwayAttentionNetworksforModelingSentencePairs.pdf 199KB Learning deep structured semantic models for web search using clickthrough.pdf 435KB Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks.pdf 654KB data_prepare.py 2KB .idea workspace.xml 40KB misc.xml 203B modules.xml 278B text_matching.iml 586B ss.md 0B paircnn_ranking infer.py 2KB result.txt 458B train.py 6KB __pycache__ PairCNN_Ranking.cpython-35.pyc 4KB PairCNN_Ranking.py 7KB __pycache__ data_prepare.cpython-35.pyc 3KB config.cpython-35.pyc 669B README.md 475B config.py 350B资源评论
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