利用Python实现中文文本关键词抽取，分别采用TF-IDF、TextRank、Word2Vec词聚类三种方法。
神策杯2018高校算法大师赛（中文关键词提取）第二名代码方案
Implementation of algorithm in keyword extraction,including TextRank,TF-IDF and the combination of both
Different datasets for developing and testing keyword extraction algorithms
Keyword extraction using TextRank algorithm after pre-processing the text with lemmatization, filtering unwanted parts-of-speech and other techniques.
A keyword and phrase extraction library based on the Rapid Automatic Keyword Extraction algorithm (RAKE).
Keyword extraction with Word2Vec
Python library for keyword extraction
Automatic keyword extraction - no alchemy required!
Multilingual Rapid Automatic Keyword Extraction (RAKE) for Python
keyword extraction and summarization for Chinese text by TextRank
BERT, LDA, and TFIDF based keyword extraction in Python
关键词抽取，神策杯2018高校算法大师赛比赛，solo 排名3/591
Python实现中文文本关键词抽取，分别用了TF-IDF、LDA、RNN、LSTM和LR-SGD两类共五种方法，全网最全没有之一。
Python实现中文文本关键词抽取，分别用了TF-IDF、LDA、RNN、LSTM和LR-SGD两类共五种方法，全网最全没有之一。
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。