Vector Space Modeling (20%)

handle large text collections, using data streaming and efficient incremental algorithms, which differentiates it from most other scientific software packages that only target batch and in-memory proc

Gensim

REF：

以 gensim 訓練中文詞向量雷德麥的藏書閣

基于 Gensim 的 Word2Vec 实践SegmentFault 思否

以 jieba 與 gensim 探索文本主題：五月天人生無限公司歌詞分析 ( II)Medium

以 jieba 與 gensim 探索文本主題：五月天人生無限公司歌詞分析 ( I )Medium

類神經網路 -- word2vec (part 1 : Overview) « MARK CHANG'S BLOG

自然語言處理 -- Vector Space of Semantics « MARK CHANG'S BLOG

sklearn features extract

http://sklearn.lzjqsdd.com/modules/feature_extraction.htmlsklearn.lzjqsdd.com

REF

Gensim Fasttext pre-trained model get vectors for out-of-vocabulary words

out-of-vocab words are represented as the sum of character ngram vectors. While the intent is to handle out-of-vocab words (unks) like "blargfizzle", it also handles phrases like your input.

https://stackoverflow.com/questions/50828314/how-does-the-gensim-fasttext-pre-trained-model-get-vectors-for-out-of-vocabulary

BERT

GitHub - google-research/bert: TensorFlow code and pre-trained models for BERTGitHub

BERT相关论文、文章和代码资源汇总我爱自然语言处理

干货 | BERT fine-tune 终极实践教程简书

【NLP】BERT中文实战踩坑 - 掘金

文本相似度

BERT中文实战（文本相似度）_sliderSun的博客-CSDN博客_中文bert

Getting started with Word2Vec

Getting started with Word2VecTextProcessing

Word2vec Made Easy

Word2vec Made EasyMedium

全面擁抱Transformer：NLP三大特徵抽取器（CNN/RNN/TF）比較

https://blog.csdn.net/dQCFKyQDXYm3F8rB0/article/details/86446077

five most popular Similarity Measures in Python

机器学习各种相似性度量及Python实现_赵大寳Note的博客-CSDN博客_python 相似性度量

Implementing the five most popular Similarity Measures in PythonBig Data Made Simple