短文本相似度计算

短文本相似度计算方法

* 最长公共子序列
* 编辑距离
* 相同单词个数/序列长度
* word2vec+余弦相似度
* Sentence2Vector
https://blog.csdn.net/qjzcy/article/details/51882959?spm=0.0.0.0.zFx7Qk
<https://blog.csdn.net/qjzcy/article/details/51882959?spm=0.0.0.0.zFx7Qk>
*
DSSM(deep structured semantic models)(BOW/CNN/RNN)
https://www.cnblogs.com/qniguoym/p/7772561.html
<https://www.cnblogs.com/qniguoym/p/7772561.html>

*
lstm+topic
https://blog.csdn.net/qjzcy/article/details/52269382
<https://blog.csdn.net/qjzcy/article/details/52269382>

百度AI的例子:
http://ai.baidu.com/tech/nlp/simnet <http://ai.baidu.com/tech/nlp/simnet>
http://ai.baidu.com/docs#/NLP-API/c150c35a
<http://ai.baidu.com/docs#/NLP-API/c150c35a>

文本分类

* 贝叶斯
* 支持向量
* 逻辑回归
*
http://sklearn.apachecn.org/cn/0.19.0/auto_examples/text/document_classification_20newsgroups.html#sphx-glr-auto-examples-text-document-classification-20newsgroups-py

<http://sklearn.apachecn.org/cn/0.19.0/auto_examples/text/document_classification_20newsgroups.html#sphx-glr-auto-examples-text-document-classification-20newsgroups-py>
* fasttext
* bilstm
* cnn
* rcnn
* https://github.com/keras-team/keras/tree/master/examples
<https://github.com/keras-team/keras/tree/master/examples>
序列标注

* HMM
* CRF
* LSTM+CRF
* seq2seq
* seq2seq+attention

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