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Jcseg

Jcseg is an Apache-2.0-licensed Java NLP library for CJK and English text segmentation, with keyword, key-phrase, key-sentence and automatic-summary extraction. It also supplies a Jetty-based HTTP server and integrations for Lucene, Solr, Elasticsearch and OpenSearch.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Jcseg — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use Jcseg when a Java application or search stack needs configurable CJK-aware tokenization, or when text-processing functions should be exposed through its HTTP server.

Who it is for

  • Java developers building Chinese or CJK text-processing features.
  • Search teams adding language analysis to Lucene, Solr, Elasticsearch or OpenSearch.
  • Developers who want to call text segmentation and extraction from clients written in other languages through an HTTP service.

Documented uses

  • Split Chinese, CJK and English text into tokens for downstream processing or retrieval.
  • Extract keywords, key phrases and key sentences from documents.
  • Generate automatic text summaries.
  • Recognize dictionary-supported entities such as names, places, URLs and email addresses.
  • Configure vocabulary and segmentation behavior for a text-processing workflow.
Before you choose

Requirements & limits

The public GitHub repository lists an Apache-2.0 license.

  • The README describes seven segmentation modes, including fine-grained retrieval output, dictionary-only detection and general n-gram segmentation.
  • Custom dictionaries and configuration options support adjustments to vocabulary and processing behavior.
  • The project documents Java library use, search-engine analyzer integrations and a Jetty-based HTTP service as distinct integration routes.
  • The README cautions that dictionary-based part-of-speech tagging is not ideal when high accuracy is required.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Try Jcseg's interactive segmentation demo

Build the project and use its terminal demo to inspect text segmentation and extraction modes.

Before you start

  • A checkout of the Jcseg repository.
  • Apache Ant or Maven.
  • Java to run the packaged JAR.

Steps

  1. From the Jcseg root directory, build with ant all or use Maven.

  2. Run java -jar jcseg-core-{version}.jar with the version matching the built JAR.

  3. Enter text at the prompt; use :seg_mode to switch segmentation modes or :keywords, :keyphrase, :sentence, and :summary to select extraction modes.

Expected outcome

The terminal demo displays results for the selected segmentation or extraction mode.

Guide limitations

  • The README documents a demo workflow, not a production deployment procedure.
  • The project warns that its dictionary-based part-of-speech tagging may not suit applications requiring high accuracy.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
16 October 2026
Original website title
lionsoul2014/jcseg · Official homepage title · retained in its source language
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