NLPchina/ansj_seg
ansj分词.ict的真正java实现.分词效果速度都超过开源版的ict. 中文分词,人名识别,词性标注,用户自定义词典 observed · 2026-08-28
Health v2 · maintenance only
23/100
- Activity 0
- Release rhythm 8
- Longevity 100
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 5110
- days_rel: n/a
- days_push: 1018
- n_releases_24m: 0
Adoption not part of the score
6517 stars · 2267 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
A Java library for Chinese word segmentation based on n-Gram+CRF+HMM, achieving ~2 million characters/second with 96%+ accuracy. It also provides Chinese name recognition, part-of-speech tagging, custom dictionaries, keyword extraction, and automatic summarization.
Use cases
- segment chinese text into words
- tokenize chinese sentences in java
- recognize chinese person names in text
- add custom domain dictionary to a chinese tokenizer
- extract keywords from chinese documents
- generate automatic summaries of chinese text
- tag parts of speech for chinese words
When to choose
- you need fast, high-accuracy chinese word segmentation on the JVM
- you want user-defined dictionaries and name recognition out of the box
- your project is Java/Maven-based and needs a pure-Java ict-class segmentation solution
When to avoid
- you need segmentation for languages other than chinese
- you want state-of-the-art neural (LSTM/transformer) segmentation models
- you need a library with frequent updates and active community support
Facets
library · maturity maintenance
nlp parser localization jvm chinese-word-segmentation part-of-speech-tagging named-entity-recognition custom-dictionary keyword-extraction text-summarization natural-language-processing
1 source
- readme: https://github.com/NLPchina/ansj_seg · fetched 2026-08-28 · 878c96754bdf
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| NLPchina/ansj_seg | main | 23 |
For agents
markdown · JSON · MCP: product_card(name="NLPchina/ansj_seg")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem