531 lines
13 KiB
Go
531 lines
13 KiB
Go
// Copyright 2013 Hui Chen
|
|
// Copyright 2016 ego authors
|
|
//
|
|
// Licensed under the Apache License, Version 2.0 (the "License"): you may
|
|
// not use this file except in compliance with the License. You may obtain
|
|
// a copy of the License at
|
|
//
|
|
// http://www.apache.org/licenses/LICENSE-2.0
|
|
//
|
|
// Unless required by applicable law or agreed to in writing, software
|
|
// distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
|
|
// WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
|
|
// License for the specific language governing permissions and limitations
|
|
// under the License.
|
|
|
|
/*
|
|
|
|
package gse Go efficient text segmentation, Go 语言分词
|
|
*/
|
|
|
|
package gse
|
|
|
|
import (
|
|
"bufio"
|
|
"fmt"
|
|
"io"
|
|
"log"
|
|
"math"
|
|
"os"
|
|
"path"
|
|
"runtime"
|
|
"strconv"
|
|
"strings"
|
|
"unicode"
|
|
"unicode/utf8"
|
|
)
|
|
|
|
const (
|
|
version string = "v0.10.0.106, Danube River!"
|
|
|
|
minTokenFrequency = 2 // 仅从字典文件中读取大于等于此频率的分词
|
|
)
|
|
|
|
// GetVersion get the gse version
|
|
func GetVersion() string {
|
|
return version
|
|
}
|
|
|
|
// Segmenter 分词器结构体
|
|
type Segmenter struct {
|
|
dict *Dictionary
|
|
}
|
|
|
|
// jumper 该结构体用于记录 Viterbi 算法中某字元处的向前分词跳转信息
|
|
type jumper struct {
|
|
minDistance float32
|
|
token *Token
|
|
}
|
|
|
|
// Dictionary 返回分词器使用的词典
|
|
func (seg *Segmenter) Dictionary() *Dictionary {
|
|
return seg.dict
|
|
}
|
|
|
|
// getCurrentFilePath get current file path
|
|
func getCurrentFilePath() string {
|
|
_, filePath, _, _ := runtime.Caller(1)
|
|
return filePath
|
|
}
|
|
|
|
// Read read the dict flie
|
|
func (seg *Segmenter) Read(file string) error {
|
|
log.Printf("Load the gse dictionary: \"%s\" ", file)
|
|
dictFile, err := os.Open(file)
|
|
if err != nil {
|
|
log.Printf("Could not load dictionaries: \"%s\", %v \n", file, err)
|
|
return err
|
|
}
|
|
defer dictFile.Close()
|
|
|
|
reader := bufio.NewReader(dictFile)
|
|
var (
|
|
text string
|
|
freqText string
|
|
frequency int
|
|
pos string
|
|
)
|
|
|
|
// 逐行读入分词
|
|
line := 0
|
|
for {
|
|
line++
|
|
size, fsErr := fmt.Fscanln(reader, &text, &freqText, &pos)
|
|
if fsErr != nil {
|
|
if fsErr == io.EOF {
|
|
// End of file
|
|
break
|
|
}
|
|
|
|
if size > 0 {
|
|
log.Printf("File '%v' line \"%v\" read error: %v, skip",
|
|
file, line, fsErr.Error())
|
|
} else {
|
|
log.Printf("File '%v' line \"%v\" is empty, read error: %v, skip",
|
|
file, line, fsErr.Error())
|
|
}
|
|
}
|
|
|
|
if size == 0 {
|
|
// 文件结束或错误行
|
|
// break
|
|
continue
|
|
} else if size < 2 {
|
|
// 无效行
|
|
continue
|
|
} else if size == 2 {
|
|
// 没有词性标注时设为空字符串
|
|
pos = ""
|
|
}
|
|
|
|
// 解析词频
|
|
var err error
|
|
frequency, err = strconv.Atoi(freqText)
|
|
if err != nil {
|
|
continue
|
|
}
|
|
|
|
// 过滤频率太小的词
|
|
if frequency < minTokenFrequency {
|
|
continue
|
|
}
|
|
// 过滤, 降低词频
|
|
if len([]rune(text)) < 2 {
|
|
// continue
|
|
frequency = 2
|
|
}
|
|
|
|
// 将分词添加到字典中
|
|
words := splitTextToWords([]byte(text))
|
|
token := Token{text: words, frequency: frequency, pos: pos}
|
|
seg.dict.addToken(token)
|
|
}
|
|
|
|
return nil
|
|
}
|
|
|
|
// DictPaths get the dict's paths
|
|
func DictPaths(dictDir, filePath string) (files []string) {
|
|
var dictPath string
|
|
|
|
if filePath == "en" {
|
|
return
|
|
}
|
|
|
|
if filePath == "zh" {
|
|
dictPath = path.Join(dictDir, "dict/dictionary.txt")
|
|
files = []string{dictPath}
|
|
|
|
return
|
|
}
|
|
|
|
if filePath == "jp" {
|
|
dictPath = path.Join(dictDir, "dict/jp/dict.txt")
|
|
files = []string{dictPath}
|
|
|
|
return
|
|
}
|
|
|
|
// if strings.Contains(filePath, ",") {
|
|
fileName := strings.Split(filePath, ",")
|
|
for i := 0; i < len(fileName); i++ {
|
|
if fileName[i] == "jp" {
|
|
dictPath = path.Join(dictDir, "dict/jp/dict.txt")
|
|
}
|
|
|
|
if fileName[i] == "zh" {
|
|
dictPath = path.Join(dictDir, "dict/dictionary.txt")
|
|
}
|
|
|
|
// if str[i] == "ti" {
|
|
// }
|
|
|
|
dictName := fileName[i] != "en" && fileName[i] != "zh" &&
|
|
fileName[i] != "jp" && fileName[i] != "ti"
|
|
|
|
if dictName {
|
|
dictPath = fileName[i]
|
|
}
|
|
|
|
if dictPath != "" {
|
|
files = append(files, dictPath)
|
|
}
|
|
}
|
|
// }
|
|
log.Println("Dict files path: ", files)
|
|
|
|
return
|
|
}
|
|
|
|
// IsJp is jp char return true
|
|
func IsJp(segText string) bool {
|
|
for _, r := range segText {
|
|
jp := unicode.Is(unicode.Scripts["Hiragana"], r) ||
|
|
unicode.Is(unicode.Scripts["Katakana"], r)
|
|
if jp {
|
|
return true
|
|
}
|
|
}
|
|
return false
|
|
}
|
|
|
|
// SegToken add segmenter token
|
|
func (seg *Segmenter) SegToken() {
|
|
// 计算每个分词的路径值,路径值含义见 Token 结构体的注释
|
|
logTotalFrequency := float32(math.Log2(float64(seg.dict.totalFrequency)))
|
|
for i := range seg.dict.tokens {
|
|
token := &seg.dict.tokens[i]
|
|
token.distance = logTotalFrequency - float32(math.Log2(float64(token.frequency)))
|
|
}
|
|
|
|
// 对每个分词进行细致划分,用于搜索引擎模式,
|
|
// 该模式用法见 Token 结构体的注释。
|
|
for i := range seg.dict.tokens {
|
|
token := &seg.dict.tokens[i]
|
|
segments := seg.segmentWords(token.text, true)
|
|
|
|
// 计算需要添加的子分词数目
|
|
numTokensToAdd := 0
|
|
for iToken := 0; iToken < len(segments); iToken++ {
|
|
// if len(segments[iToken].token.text) > 1 {
|
|
// 略去字元长度为一的分词
|
|
// TODO: 这值得进一步推敲,特别是当字典中有英文复合词的时候
|
|
if len(segments[iToken].token.text) > 0 {
|
|
hasJp := false
|
|
if len(segments[iToken].token.text) == 1 {
|
|
segText := string(segments[iToken].token.text[0])
|
|
hasJp = IsJp(segText)
|
|
}
|
|
|
|
if !hasJp {
|
|
numTokensToAdd++
|
|
}
|
|
}
|
|
}
|
|
token.segments = make([]*Segment, numTokensToAdd)
|
|
|
|
// 添加子分词
|
|
iSegmentsToAdd := 0
|
|
for iToken := 0; iToken < len(segments); iToken++ {
|
|
// if len(segments[iToken].token.text) > 1 {
|
|
if len(segments[iToken].token.text) > 0 {
|
|
hasJp := false
|
|
if len(segments[iToken].token.text) == 1 {
|
|
segText := string(segments[iToken].token.text[0])
|
|
hasJp = IsJp(segText)
|
|
}
|
|
|
|
if !hasJp {
|
|
token.segments[iSegmentsToAdd] = &segments[iToken]
|
|
iSegmentsToAdd++
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
}
|
|
|
|
// LoadDict load the dictionary from the file
|
|
//
|
|
// The format of the dictionary is (one for each participle):
|
|
// participle text, frequency, part of speech
|
|
//
|
|
// Can load multiple dictionary files, the file name separated by ","
|
|
// the front of the dictionary preferentially load the participle,
|
|
// such as: "user_dictionary.txt,common_dictionary.txt"
|
|
// When a participle appears both in the user dictionary and
|
|
// in the `common dictionary`, the `user dictionary` is given priority.
|
|
//
|
|
// 从文件中载入词典
|
|
//
|
|
// 可以载入多个词典文件,文件名用 "," 分隔,排在前面的词典优先载入分词,比如:
|
|
// "用户词典.txt,通用词典.txt"
|
|
// 当一个分词既出现在用户词典也出现在 `通用词典` 中,则优先使用 `用户词典`。
|
|
//
|
|
// 词典的格式为(每个分词一行):
|
|
// 分词文本 频率 词性
|
|
func (seg *Segmenter) LoadDict(files ...string) error {
|
|
seg.dict = NewDict()
|
|
|
|
var (
|
|
dictDir = path.Join(path.Dir(getCurrentFilePath()), "data")
|
|
dictPath string
|
|
// load bool
|
|
)
|
|
|
|
if len(files) > 0 {
|
|
dictFiles := DictPaths(dictDir, files[0])
|
|
if len(dictFiles) > 0 {
|
|
// load = true
|
|
// files = dictFiles
|
|
for i := 0; i < len(dictFiles); i++ {
|
|
err := seg.Read(dictFiles[i])
|
|
if err != nil {
|
|
return err
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
if len(files) == 0 {
|
|
dictPath = path.Join(dictDir, "dict/dictionary.txt")
|
|
// files = []string{dictPath}
|
|
err := seg.Read(dictPath)
|
|
if err != nil {
|
|
return err
|
|
}
|
|
}
|
|
|
|
// if files[0] != "" && files[0] != "en" && !load {
|
|
// for _, file := range strings.Split(files[0], ",") {
|
|
// // for _, file := range files {
|
|
// err := seg.Read(file)
|
|
// if err != nil {
|
|
// return err
|
|
// }
|
|
// }
|
|
// }
|
|
|
|
seg.SegToken()
|
|
log.Println("Gse dictionary loaded finished.")
|
|
|
|
return nil
|
|
}
|
|
|
|
// Segment 对文本分词
|
|
//
|
|
// 输入参数:
|
|
// bytes UTF8 文本的字节数组
|
|
//
|
|
// 输出:
|
|
// []Segment 划分的分词
|
|
func (seg *Segmenter) Segment(bytes []byte) []Segment {
|
|
return seg.internalSegment(bytes, false)
|
|
}
|
|
|
|
// ModeSegment segment using search mode if searchMode is true
|
|
func (seg *Segmenter) ModeSegment(bytes []byte, searchMode ...bool) []Segment {
|
|
var mode bool
|
|
if len(searchMode) > 0 {
|
|
mode = searchMode[0]
|
|
}
|
|
|
|
return seg.internalSegment(bytes, mode)
|
|
}
|
|
|
|
// Slice use modeSegment segment retrun []string
|
|
// using search mode if searchMode is true
|
|
func (seg *Segmenter) Slice(bytes []byte, searchMode ...bool) []string {
|
|
segs := seg.ModeSegment(bytes, searchMode...)
|
|
return ToSlice(segs, searchMode...)
|
|
}
|
|
|
|
// Slice use modeSegment segment retrun string
|
|
// using search mode if searchMode is true
|
|
func (seg *Segmenter) String(bytes []byte, searchMode ...bool) string {
|
|
segs := seg.ModeSegment(bytes, searchMode...)
|
|
return ToString(segs, searchMode...)
|
|
}
|
|
|
|
func (seg *Segmenter) internalSegment(bytes []byte, searchMode bool) []Segment {
|
|
// 处理特殊情况
|
|
if len(bytes) == 0 {
|
|
// return []Segment{}
|
|
return nil
|
|
}
|
|
|
|
// 划分字元
|
|
text := splitTextToWords(bytes)
|
|
|
|
return seg.segmentWords(text, searchMode)
|
|
}
|
|
|
|
func (seg *Segmenter) segmentWords(text []Text, searchMode bool) []Segment {
|
|
// 搜索模式下该分词已无继续划分可能的情况
|
|
if searchMode && len(text) == 1 {
|
|
return nil
|
|
}
|
|
|
|
// jumpers 定义了每个字元处的向前跳转信息,
|
|
// 包括这个跳转对应的分词,
|
|
// 以及从文本段开始到该字元的最短路径值
|
|
jumpers := make([]jumper, len(text))
|
|
|
|
if seg.dict == nil {
|
|
return nil
|
|
}
|
|
|
|
tokens := make([]*Token, seg.dict.maxTokenLen)
|
|
for current := 0; current < len(text); current++ {
|
|
// 找到前一个字元处的最短路径,以便计算后续路径值
|
|
var baseDistance float32
|
|
if current == 0 {
|
|
// 当本字元在文本首部时,基础距离应该是零
|
|
baseDistance = 0
|
|
} else {
|
|
baseDistance = jumpers[current-1].minDistance
|
|
}
|
|
|
|
// 寻找所有以当前字元开头的分词
|
|
numTokens := seg.dict.lookupTokens(
|
|
text[current:minInt(current+seg.dict.maxTokenLen, len(text))], tokens)
|
|
|
|
// 对所有可能的分词,更新分词结束字元处的跳转信息
|
|
for iToken := 0; iToken < numTokens; iToken++ {
|
|
location := current + len(tokens[iToken].text) - 1
|
|
if !searchMode || current != 0 || location != len(text)-1 {
|
|
updateJumper(&jumpers[location], baseDistance, tokens[iToken])
|
|
}
|
|
}
|
|
|
|
// 当前字元没有对应分词时补加一个伪分词
|
|
if numTokens == 0 || len(tokens[0].text) > 1 {
|
|
updateJumper(&jumpers[current], baseDistance,
|
|
&Token{text: []Text{text[current]}, frequency: 1, distance: 32, pos: "x"})
|
|
}
|
|
}
|
|
|
|
// 从后向前扫描第一遍得到需要添加的分词数目
|
|
numSeg := 0
|
|
for index := len(text) - 1; index >= 0; {
|
|
location := index - len(jumpers[index].token.text) + 1
|
|
numSeg++
|
|
index = location - 1
|
|
}
|
|
|
|
// 从后向前扫描第二遍添加分词到最终结果
|
|
outputSegments := make([]Segment, numSeg)
|
|
for index := len(text) - 1; index >= 0; {
|
|
location := index - len(jumpers[index].token.text) + 1
|
|
numSeg--
|
|
outputSegments[numSeg].token = jumpers[index].token
|
|
index = location - 1
|
|
}
|
|
|
|
// 计算各个分词的字节位置
|
|
bytePosition := 0
|
|
for iSeg := 0; iSeg < len(outputSegments); iSeg++ {
|
|
outputSegments[iSeg].start = bytePosition
|
|
bytePosition += textSliceByteLen(outputSegments[iSeg].token.text)
|
|
outputSegments[iSeg].end = bytePosition
|
|
}
|
|
return outputSegments
|
|
}
|
|
|
|
// updateJumper 更新跳转信息:
|
|
// 1. 当该位置从未被访问过时 (jumper.minDistance 为零的情况),或者
|
|
// 2. 当该位置的当前最短路径大于新的最短路径时
|
|
// 将当前位置的最短路径值更新为 baseDistance 加上新分词的概率
|
|
func updateJumper(jumper *jumper, baseDistance float32, token *Token) {
|
|
newDistance := baseDistance + token.distance
|
|
if jumper.minDistance == 0 || jumper.minDistance > newDistance {
|
|
jumper.minDistance = newDistance
|
|
jumper.token = token
|
|
}
|
|
}
|
|
|
|
// minInt 取两整数较小值
|
|
func minInt(a, b int) int {
|
|
if a > b {
|
|
return b
|
|
}
|
|
return a
|
|
}
|
|
|
|
// maxInt 取两整数较大值
|
|
func maxInt(a, b int) int {
|
|
if a > b {
|
|
return a
|
|
}
|
|
return b
|
|
}
|
|
|
|
// splitTextToWords 将文本划分成字元
|
|
func splitTextToWords(text Text) []Text {
|
|
output := make([]Text, 0, len(text)/3)
|
|
current := 0
|
|
inAlphanumeric := true
|
|
alphanumericStart := 0
|
|
for current < len(text) {
|
|
r, size := utf8.DecodeRune(text[current:])
|
|
if size <= 2 && (unicode.IsLetter(r) || unicode.IsNumber(r)) {
|
|
// 当前是拉丁字母或数字(非中日韩文字)
|
|
if !inAlphanumeric {
|
|
alphanumericStart = current
|
|
inAlphanumeric = true
|
|
}
|
|
} else {
|
|
if inAlphanumeric {
|
|
inAlphanumeric = false
|
|
if current != 0 {
|
|
output = append(output, toLower(text[alphanumericStart:current]))
|
|
}
|
|
}
|
|
output = append(output, text[current:current+size])
|
|
}
|
|
current += size
|
|
}
|
|
|
|
// 处理最后一个字元是英文的情况
|
|
if inAlphanumeric {
|
|
if current != 0 {
|
|
output = append(output, toLower(text[alphanumericStart:current]))
|
|
}
|
|
}
|
|
|
|
return output
|
|
}
|
|
|
|
// toLower 将英文词转化为小写
|
|
func toLower(text []byte) []byte {
|
|
output := make([]byte, len(text))
|
|
for i, t := range text {
|
|
if t >= 'A' && t <= 'Z' {
|
|
output[i] = t - 'A' + 'a'
|
|
} else {
|
|
output[i] = t
|
|
}
|
|
}
|
|
return output
|
|
}
|