# huichen/sego

Go中文分词

Repository: https://github.com/huichen/sego
Canonical: https://ross.abutalabs.com/products/sego
Language: Go
License: NOASSERTION
License Family: other
Last push: 2022-11-16T02:13:58+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": 4793, "days_push": 1387, "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 1826, forks 353 (observed 2026-08-28T04:05:41.366657+00:00)

## What it is
sego is a Go library for Chinese word segmentation using a double-array trie dictionary and a shortest-path-plus-dynamic-programming algorithm. It supports normal and search-engine segmentation modes, user dictionaries, part-of-speech tagging, and can run as a JSON RPC service.

## Use cases
- segment Chinese text into words in Go
- tokenize Chinese documents for full-text search indexing
- add custom words to a Chinese segmentation dictionary
- run Chinese word segmentation as an RPC service
- tag parts of speech for segmented Chinese words

## When to choose
- you need fast, pure-Go Chinese word segmentation without external dependencies
- you are building a Chinese search engine and need search-mode tokenization
- you want a simple embeddable segmenter with user dictionary support

## When to avoid
- you need actively maintained NLP tooling or modern segmentation models
- you need segmentation for languages other than Chinese
- you want deep-learning-based segmentation accuracy

## Facets
- artifact type: library
- maturity: maintenance
- function: nlp, parser, search-engine
- domain: developer-tools
- platform: go, cross-platform
- tags: chinese-word-segmentation, double-array-trie, tokenization, text-segmentation, natural-language-processing, search

## Member repositories
- huichen/sego (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:41.366657+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 2026-08-30T03:19:34.339880+00:00, confidence not recorded.
  - readme: https://github.com/huichen/sego (fetched 2026-08-28T04:05:41.366657+00:00, sha f57edcc66f08)
- Data as of 2026-08-30T08:39:29.467469+00:00.