gse alternatives and similar packages
Based on the "Natural Language Processing" category.
Alternatively, view gse alternatives based on common mentions on social networks and blogs.
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prose
:book: A Golang library for text processing, including tokenization, part-of-speech tagging, and named-entity extraction. -
spaGO
Self-contained Machine Learning and Natural Language Processing library in Go -
universal-translator
:speech_balloon: i18n Translator for Go/Golang using CLDR data + pluralization rules -
locales
:earth_americas: a set of locales generated from the CLDR Project which can be used independently or within an i18n package; these were built for use with, but not exclusive to https://github.com/go-playground/universal-translator -
go-nlp
Utilities for working with discrete probability distributions and other tools useful for doing NLP work. -
segment
A Go library for performing Unicode Text Segmentation as described in Unicode Standard Annex #29 -
textcat
A Go package for n-gram based text categorization, with support for utf-8 and raw text -
go-localize
i18n (Internationalization and localization) engine written in Go, used for translating locale strings. -
stemmer
Stemmer packages for Go programming language. Includes English, German and Dutch stemmers. -
petrovich
Golang port of Petrovich - an inflector for Russian anthroponyms. -
go-tinydate
A tiny date object in Go. Tinydate uses only 4 bytes of memory -
golibstemmer
Go bindings for the snowball libstemmer library including porter 2 -
gotokenizer
A tokenizer based on the dictionary and Bigram language models for Go. (Now only support chinese segmentation) -
spreak
Flexible translation and humanization library for Go, based on the concepts behind gettext.
Access the most powerful time series database as a service
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They vary from L1 to L5 with "L5" being the highest.
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README
gse
Go efficient multilingual NLP and text segmentation; support English, Chinese, Japanese and others. And supports with elasticsearch and bleve.
<!----> <!---->
Gse is implements jieba by golang, and try add NLP support and more feature
Feature:
- Support common, search engine, full mode, precise mode and HMM mode multiple word segmentation modes;
- Support user and embed dictionary, Part-of-speech/POS tagging, analyze segment info, stop and trim words
- Support multilingual: English, Chinese, Japanese and others
- Support Traditional Chinese
- Support HMM cut text use Viterbi algorithm
- Support NLP by TensorFlow (in work)
- Named Entity Recognition (in work)
- Supports with elasticsearch and bleve
- run JSON RPC service.
Algorithm:
- Dictionary with double array trie (Double-Array Trie) to achieve
- Segmenter algorithm is the shortest path (based on word frequency and dynamic programming), and DAG and HMM algorithm word segmentation.
Text Segmentation speed:
- single thread 9.2MB/s
- goroutines concurrent 26.8MB/s.
- HMM text segmentation single thread 3.2MB/s. (2core 4threads Macbook Pro).
Binding:
gse-bind, binding JavaScript and other, support more language.
Install / update
With Go module support (Go 1.11+), just import:
import "github.com/go-ego/gse"
Otherwise, to install the gse package, run the command:
go get -u github.com/go-ego/gse
Use
package main
import (
"fmt"
"regexp"
"github.com/go-ego/gse"
"github.com/go-ego/gse/hmm/pos"
)
var (
text = "Hello world, Helloworld. Winter is coming! こんにちは世界, 你好世界."
new, _ = gse.New("zh,testdata/test_dict3.txt", "alpha")
seg gse.Segmenter
posSeg pos.Segmenter
)
func main() {
// Loading the default dictionary
seg.LoadDict()
// Loading the default dictionary with embed
// seg.LoadDictEmbed()
//
// Loading the Simplified Chinese dictionary
// seg.LoadDict("zh_s")
// seg.LoadDictEmbed("zh_s")
//
// Loading the Traditional Chinese dictionary
// seg.LoadDict("zh_t")
//
// Loading the Japanese dictionary
// seg.LoadDict("jp")
//
// Load the dictionary
// 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)
pos.WithGse(seg)
po = posSeg.Cut(text, true)
fmt.Println("pos: ", po)
po = posSeg.TrimWithPos(po, "zg")
fmt.Println("trim pos: ", po)
}
func segCut() {
// Text Segmentation
tb := []byte(text)
fmt.Println(seg.String(text, true))
segments := seg.Segment(tb)
// Handle word segmentation results, search mode
fmt.Println(gse.ToString(segments, true))
}
Look at an custom dictionary example
package main
import (
"fmt"
_ "embed"
"github.com/go-ego/gse"
)
//go:embed test_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 := "Hello world, こんにちは世界, 你好世界!"
s1 := seg.Cut(text1, true)
fmt.Println(s1)
fmt.Println("trim: ", seg.Trim(s1))
fmt.Println("stop: ", seg.Stop(s1))
fmt.Println(seg.String(text1, true))
segments := seg.Segment([]byte(text1))
fmt.Println(gse.ToString(segments))
}
Elasticsearch
How to use it with elasticsearch?
Authors
License
Gse is primarily distributed under the terms of "both the MIT license and the Apache License (Version 2.0)". See LICENSE-APACHE, LICENSE-MIT.
*Note that all licence references and agreements mentioned in the gse README section above
are relevant to that project's source code only.