yanyiwu/nodejieba

"结巴"中文分词的Node.js版本

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Summary Information

Updated 1 hour ago
Added to GitGenius on September 21st, 2026
Created on January 23rd, 2014
Open Issues & Pull Requests: 4 (+0)
GitHub issues: Enabled
Number of forks: 287
Total Stargazers: 3,232 (+0)
Total Subscribers: 67 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 14.4 days
Mean response time: 111.5 days
90th percentile: 423.2 days
Tracked items: 73

Maintainer activity

1 person did triage or write work on this repository in the last 12 months.

Counts unlabeled, assigned, unassigned, milestoned, demilestoned, locked, unlocked over the last 12 months. These are issue and pull request events that require triage or write permission. Commits and code review are not counted. labeled and renamed are excluded because GitHub issue forms record the issue author as the actor. Figures from October 11, 2026. This count is not comparable across projects: each project's automation decides which of these events a person emits.

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Issue Activity (beta)

Open issues: 1
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 105 days
Stale 30+ days: 1
Stale 90+ days: 1

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • Stale (85)
  • enhancement (1)

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Detailed Description

nodejieba is a Node.js binding for Chinese word segmentation that brings the Jieba tokenizer to JavaScript environments.

The tool addresses the challenge of breaking Chinese text into meaningful words, a task that differs fundamentally from space-delimited word splitting in English. Jieba performs this segmentation by combining dictionary-based matching with dynamic programming and hidden Markov models to handle both known words and out-of-vocabulary terms. The Node.js binding wraps the underlying C++ implementation, allowing developers to use this segmentation capability directly within Node.js applications without calling external processes.

Developers working with Chinese language processing in Node.js should consider this tool if they need accurate word segmentation as a preprocessing step for search, text analysis, or natural language processing pipelines. The project suits applications that require handling of modern Chinese text where simple character-by-character or whitespace-based approaches would lose semantic meaning. The binding approach means performance characteristics are closer to native implementations than pure JavaScript alternatives would be.

The project shows consistent maintenance with regular updates addressing issues and improvements. Development activity demonstrates responsiveness to user-reported problems and feature requests. The codebase receives ongoing refinement to ensure compatibility and stability across Node.js versions.