rake-nltk总结

RAKE是快速自动关键字提取算法(Rapid Automatic Keyword Extraction algorithm)的简称，是一种独立于域的关键字提取算法，它通过分析文字出现的频率及其与文本中其他词的共现来尝试确定文本主体中的关键短语。

from rake_nltk import Rake

# Uses stopwords for english from NLTK, and all puntuation characters by
# default
r = Rake()

# Extraction given the text.
r.extract_keywords_from_text()

# Extraction given the list of strings where each string is a sentence.
r.extract_keywords_from_sentences()

# To get keyword phrases ranked highest to lowest.
r.get_ranked_phrases()

# To get keyword phrases ranked highest to lowest with scores.
r.get_ranked_phrases_with_scores()

# To use it with a specific language supported by nltk.
r = Rake(language=)

# If you want to provide your own set of stop words and punctuations to
r = Rake(
    stopwords=,
    punctuations=
)

# If you want to control the metric for ranking. Paper uses d(w)/f(w) as the
# metric. You can use this API with the following metrics:
# 1. d(w)/f(w) (Default metric) Ratio of degree of word to its frequency.
# 2. d(w) Degree of word only.
# 3. f(w) Frequency of word only.

r = Rake(ranking_metric=Metric.DEGREE_TO_FREQUENCY_RATIO)
r = Rake(ranking_metric=Metric.WORD_DEGREE)
r = Rake(ranking_metric=Metric.WORD_FREQUENCY)

# If you want to control the max or min words in a phrase, for it to be
# considered for ranking you can initialize a Rake instance as below:

r = Rake(min_length=2, max_length=4)