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huaban/jieba-analysis

结巴分词(java版) observed · 2026-08-28

github.com/huaban/jieba-analysis · homepage · Java · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 4775
  • days_rel: n/a
  • days_push: 784
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

2709 stars · 848 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Java port of the popular jieba Chinese word segmentation library, supporting search and index segmentation modes, user dictionaries, and TF-IDF keyword extraction. It uses trie-based DAG scanning, dynamic programming, and HMM/Viterbi for unknown word recognition.

Use cases

  • segment chinese text into words in java
  • tokenize chinese text for search indexing
  • extract keywords from chinese text with tfidf
  • add custom words to a chinese dictionary
  • build a chinese full-text search engine in java

When to choose

  • you need Chinese word segmentation in a JVM application
  • you want jieba-compatible segmentation or TF-IDF keyword extraction in Java
  • you need fast segmentation (millions of words per second) for search indexing

When to avoid

  • you need part-of-speech tagging, which was removed for performance
  • you are not working with Chinese text
  • you need a Python or other non-JVM implementation

Facets

library · maturity active

nlp parser search-engine jvm chinese-word-segmentation jieba tfidf keyword-extraction tokenization natural-language-processing search chinese-language

2 sources

Member repositories

RepositoryRoleHealth v2
huaban/jieba-analysismain32

For agents

markdown · JSON · MCP: product_card(name="huaban/jieba-analysis")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem