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Capsule-Text-Classification
利用keras搭建的胶囊网络(capsule network文本分类模型,包含RNN、CNN、HAN等,其中keras_utils包含了capsule层和attention层的keras实现FGN-NER
The source code of 《 FGN:Fusion Glyph Network for Chinese Named Entity Recognition 》. SOTA Chinese NER method fusing both glyph represnetation and BERT representationBERT-BiLSTM-CRF
BERT-BiLSTM-CRF的Keras版实现SMP-Keyword-Extraction
CSDN博客的关键词提取算法,融合TF,IDF,词性,位置等多特征。该项目用于参加2017 SMP用户画像测评,排名第四,在验证集中精度为59.9%,在最终集中精度为58.7%。启发式的方法,通用性强。Chinese-Character-Feature-Resource
This repo contain images,radicals,meaning radical and Pinyin for more than 6000 Chinese character. The image set inculde both traditional Chinese and simple ChineseSolr-LTR-Training
an exmaple to train LTR model and deploy it on Solr server.Bilstm-CRF-Sequence-Labeling
Tensorflow版的BiLSTM-CRF模型TEDParallelCorpusSpider
ted平行语料爬虫Love Open Source and this site? Check out how you can help us