# AimeeLee77/keyword_extraction

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。

Repository: https://github.com/AimeeLee77/keyword_extraction
Canonical: https://ross.abutalabs.com/products/keyword_extraction
Language: Python
License Family: other
Last push: 2018-01-16T01:10:56+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3206, "days_push": 3152, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1145, forks 374 (observed 2026-08-28T04:03:45.519491+00:00)

## What it is
A Python project implementing Chinese text keyword extraction using three methods: TF-IDF, TextRank, and Word2Vec word clustering. It includes a detailed tutorial-style walkthrough with sample patent text data and Chinese stopword dictionaries.

## Use cases
- extract keywords from Chinese text
- compare TF-IDF and TextRank keyword extraction
- cluster words with Word2Vec to find document keywords
- learn Chinese NLP keyword extraction in Python
- extract keywords from patent abstracts
- build Chinese word embeddings with Gensim

## When to choose
- you need to extract keywords from Chinese-language documents
- you want a learning resource explaining TF-IDF, TextRank, and Word2Vec clustering side by side
- you are working with patent or technical Chinese corpora

## When to avoid
- you need a production-ready maintained library with a license
- you need multilingual keyword extraction beyond Chinese
- you need Python 3 compatibility guarantees, since it was built on Python 2.7

## Facets
- artifact type: library
- maturity: maintenance
- function: nlp, parser, machine-learning
- domain: machine-learning
- platform: python
- tags: keyword-extraction, tf-idf, textrank, word2vec, chinese-text, jieba, gensim, text-summarization, natural-language-processing, chinese-language

## Member repositories
- AimeeLee77/keyword_extraction (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:45.519491+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:34:14.035087+00:00, confidence not recorded.
  - readme: https://github.com/AimeeLee77/keyword_extraction (fetched 2026-08-28T04:03:45.519491+00:00, sha fce692b210ef)
- Data as of 2026-08-30T08:39:29.467469+00:00.