# ysc/word

Java分布式中文分词组件 - word分词

Repository: https://github.com/ysc/word
Canonical: https://ross.abutalabs.com/products/word
Language: Java
License: Apache-2.0
License Family: permissive
Last push: 2021-03-31T09:27:08+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4551, "days_push": 1981, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1818, forks 680 (observed 2026-08-28T04:05:40.650492+00:00)

## What it is
A Java distributed Chinese word segmentation library offering multiple dictionary-based segmentation algorithms with ngram-based disambiguation. It recognizes named entities, dates, and numbers, and integrates with Lucene, Solr, and ElasticSearch.

## Use cases
- segment chinese text into words in java
- tokenize chinese for full-text search indexing
- extract named entities like person and place names from chinese text
- compute text similarity between chinese documents
- add chinese word segmentation to elasticsearch or solr
- count word frequency and tag part of speech in chinese text

## When to choose
- you need Chinese word segmentation in a JVM application
- you want Lucene, Solr, or ElasticSearch integration out of the box
- you need custom user dictionaries and multiple segmentation algorithms

## When to avoid
- you need segmentation for languages other than Chinese
- you require actively maintained software with recent updates
- you need deep-learning-based neural segmentation models

## Facets
- artifact type: library
- maturity: maintenance
- function: nlp, parser, search-engine
- domain: developer-tools
- platform: jvm, cross-platform
- tags: chinese-word-segmentation, text-similarity, lucene-integration, elasticsearch-plugin, solr-integration, ngram-model, part-of-speech-tagging, natural-language-processing, search

## Member repositories
- ysc/word (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:40.650492+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 2026-08-30T03:20:09.664728+00:00, confidence not recorded.
  - readme: https://github.com/ysc/word (fetched 2026-08-28T04:05:40.650492+00:00, sha 1ba4fd9cd635)
- Data as of 2026-08-30T08:39:29.467469+00:00.