# gse **Repository Path**: bit212/gse ## Basic Information - **Project Name**: gse - **Description**: No description available - **Primary Language**: Unknown - **License**: Apache-2.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-08-18 - **Last Updated**: 2025-08-18 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # [gse](https://github.com/go-ego/gse) Go 高性能多语言 NLP 和分词, 支持英文、中文、日文等, 支持接入 [elasticsearch](https://github.com/vcaesar/go-gse-elastic) 和 [bleve](https://github.com/vcaesar/gse-bleve) [![Build Status](https://github.com/go-ego/gse/workflows/Go/badge.svg)](https://github.com/go-ego/gse/commits/master) [![CircleCI Status](https://circleci.com/gh/go-ego/gse.svg?style=shield)](https://circleci.com/gh/go-ego/gse) [![codecov](https://codecov.io/gh/go-ego/gse/branch/master/graph/badge.svg)](https://codecov.io/gh/go-ego/gse) [![Build Status](https://travis-ci.org/go-ego/gse.svg)](https://travis-ci.org/go-ego/gse) [![Go Report Card](https://goreportcard.com/badge/github.com/go-ego/gse)](https://goreportcard.com/report/github.com/go-ego/gse) [![GoDoc](https://godoc.org/github.com/go-ego/gse?status.svg)](https://godoc.org/github.com/go-ego/gse) [![GitHub release](https://img.shields.io/github/release/go-ego/gse.svg)](https://github.com/go-ego/gse/releases/latest) [![Join the chat at https://gitter.im/go-ego/ego](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/go-ego/ego?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) Gse 是结巴分词(jieba)的 golang 实现, 并尝试添加 NLP 功能和更多属性 ## 特征: - 支持普通、搜索引擎、全模式、精确模式和 HMM 模式多种分词模式 - 支持自定义词典、embed 词典、词性标注、停用词、整理分析分词 - 多语言支持: 英文, 中文, 日文等 - 支持繁体字 - NLP 和 TensorFlow 支持 (进行中) - 命名实体识别 (进行中) - 支持接入 Elasticsearch 和 bleve - 可运行 JSON RPC 服务 ## 算法: - [词典](https://github.com/go-ego/gse/blob/master/dictionary.go)用双数组 trie(Double-Array Trie)实现, - [分词器](https://github.com/go-ego/gse/blob/master/segmenter.go)算法为基于词频的最短路径加动态规划, 以及 DAG 和 HMM 算法分词. - 支持 HMM 分词, 使用 viterbi 算法. ## 分词速度: - 单线程 9.2MB/s - goroutines 并发 26.8MB/s. - HMM 模式单线程分词速度 3.2MB/s.(双核 4 线程 Macbook Pro)。 ## Binding: [gse-bind](https://github.com/vcaesar/gse-bind), binding JavaScript and other, support more language. ## 安装/更新 With Go module support (Go 1.11+), just import: ```go import "github.com/go-ego/gse" ``` Otherwise, to install the gse package, run the command: ``` go get -u github.com/go-ego/gse ``` ## 使用 ```go package main import ( "fmt" "regexp" "github.com/go-ego/gse" "github.com/go-ego/gse/hmm/pos" ) var ( seg gse.Segmenter posSeg pos.Segmenter new, _ = gse.New("zh,testdata/test_en_dict3.txt", "alpha") text = "你好世界, Hello world, Helloworld." ) func main() { // 加载默认词典 seg.LoadDict() // 加载默认 embed 词典 // seg.LoadDictEmbed() // // 加载简体中文词典 // seg.LoadDict("zh_s") // seg.LoadDictEmbed("zh_s") // // 加载繁体中文词典 // seg.LoadDict("zh_t") // // 加载日文词典 // seg.LoadDict("jp") // // 载入词典 // seg.LoadDict("your gopath"+"/src/github.com/go-ego/gse/data/dict/dictionary.txt") cut() segCut() } func cut() { hmm := new.Cut(text, true) fmt.Println("cut use hmm: ", hmm) hmm = new.CutSearch(text, true) fmt.Println("cut search use hmm: ", hmm) fmt.Println("analyze: ", new.Analyze(hmm, text)) hmm = new.CutAll(text) fmt.Println("cut all: ", hmm) reg := regexp.MustCompile(`(\d+年|\d+月|\d+日|[\p{Latin}]+|[\p{Hangul}]+|\d+\.\d+|[a-zA-Z0-9]+)`) text1 := `헬로월드 헬로 서울, 2021年09月10日, 3.14` hmm = seg.CutDAG(text1, reg) fmt.Println("Cut with hmm and regexp: ", hmm, hmm[0], hmm[6]) } func analyzeAndTrim(cut []string) { a := seg.Analyze(cut, "") fmt.Println("analyze the segment: ", a) cut = seg.Trim(cut) fmt.Println("cut all: ", cut) fmt.Println(seg.String(text, true)) fmt.Println(seg.Slice(text, true)) } func cutPos() { po := seg.Pos(text, true) fmt.Println("pos: ", po) po = seg.TrimPos(po) fmt.Println("trim pos: ", po) posSeg.WithGse(seg) po = posSeg.Cut(text, true) fmt.Println("pos: ", po) po = posSeg.TrimWithPos(po, "zg") fmt.Println("trim pos: ", po) } func segCut() { // 分词文本 tb := []byte("山达尔星联邦共和国联邦政府") // 处理分词结果 fmt.Println("输出分词结果, 类型为字符串, 使用搜索模式: ", seg.String(tb, true)) fmt.Println("输出分词结果, 类型为 slice: ", seg.Slice(tb)) segments := seg.Segment(tb) // 处理分词结果, 普通模式 fmt.Println(gse.ToString(segments)) segments1 := seg.Segment([]byte(text)) // 搜索模式 fmt.Println(gse.ToString(segments1, true)) } ``` [自定义词典分词示例](/examples/dict/main.go) ```Go package main import ( "fmt" _ "embed" "github.com/go-ego/gse" ) //go:embed test_en_dict3.txt var testDict string func main() { // var seg gse.Segmenter // seg.LoadDict("zh, testdata/test_dict.txt, testdata/test_dict1.txt") // seg.LoadStop() seg, err := gse.NewEmbed("zh, word 20 n"+testDict, "en") // seg.LoadDictEmbed() seg.LoadStopEmbed() text1 := "所以, 你好, 再见" fmt.Println(seg.Cut(text1, true)) fmt.Println(seg.String(text1, true)) segments := seg.Segment([]byte(text1)) fmt.Println(gse.ToString(segments)) } ``` [中文分词示例](/examples/main.go) [日文分词示例](/examples/jp/main.go) ## Elasticsearch How to use it with elasticsearch? [go-gse-elastic](https://github.com/vcaesar/go-gse-elastic) ## Authors - [Maintainers](https://github.com/orgs/go-ego/people) - [Contributors](https://github.com/go-ego/gse/graphs/contributors) ## License Gse is primarily distributed under the terms of "both the MIT license and the Apache License (Version 2.0)". See [LICENSE-APACHE](http://www.apache.org/licenses/LICENSE-2.0), [LICENSE-MIT](https://github.com/go-vgo/robotgo/blob/master/LICENSE). Thanks for [sego](https://github.com/huichen/sego) and [jieba](https://github.com/fxsjy/jieba)([jiebago](https://github.com/wangbin/jiebago)).