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jieba.go
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jieba.go
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// Package jiebago is the Golang implemention of [Jieba](https://github.com/fxsjy/jieba), Python Chinese text segmentation module.
package jiebago
import (
"math"
"regexp"
"strings"
"github.com/wangbin/jiebago/dictionary"
"github.com/wangbin/jiebago/finalseg"
"github.com/wangbin/jiebago/util"
)
var (
reEng = regexp.MustCompile(`[[:alnum:]]`)
reHanCutAll = regexp.MustCompile(`(\p{Han}+)`)
reSkipCutAll = regexp.MustCompile(`[^[:alnum:]+#\n]`)
reHanDefault = regexp.MustCompile(`([\p{Han}+[:alnum:]+#&\._]+)`)
reSkipDefault = regexp.MustCompile(`(\r\n|\s)`)
)
// Segmenter is a Chinese words segmentation struct.
type Segmenter struct {
dict *Dictionary
}
// Frequency returns a word's frequency and existence
func (seg *Segmenter) Frequency(word string) (float64, bool) {
return seg.dict.Frequency(word)
}
// AddWord adds a new word with frequency to dictionary
func (seg *Segmenter) AddWord(word string, frequency float64) {
seg.dict.AddToken(dictionary.NewToken(word, frequency, ""))
}
// DeleteWord removes a word from dictionary
func (seg *Segmenter) DeleteWord(word string) {
seg.dict.AddToken(dictionary.NewToken(word, 0.0, ""))
}
/*
SuggestFrequency returns a suggested frequncy of a word or a long word
cutted into several short words.
This method is useful when a word in the sentence is not cutted out correctly.
If a word should not be further cutted, for example word "石墨烯" should not be
cutted into "石墨" and "烯", SuggestFrequency("石墨烯") will return the maximu
frequency for this word.
If a word should be further cutted, for example word "今天天气" should be
further cutted into two words "今天" and "天气", SuggestFrequency("今天", "天气")
should return the minimum frequency for word "今天天气".
*/
func (seg *Segmenter) SuggestFrequency(words ...string) float64 {
frequency := 1.0
if len(words) > 1 {
for _, word := range words {
if freq, ok := seg.dict.Frequency(word); ok {
frequency *= freq
}
frequency /= seg.dict.total
}
frequency, _ = math.Modf(frequency * seg.dict.total)
wordFreq := 0.0
if freq, ok := seg.dict.Frequency(strings.Join(words, "")); ok {
wordFreq = freq
}
if wordFreq < frequency {
frequency = wordFreq
}
} else {
word := words[0]
for segment := range seg.Cut(word, false) {
if freq, ok := seg.dict.Frequency(segment); ok {
frequency *= freq
}
frequency /= seg.dict.total
}
frequency, _ = math.Modf(frequency * seg.dict.total)
frequency += 1.0
wordFreq := 1.0
if freq, ok := seg.dict.Frequency(word); ok {
wordFreq = freq
}
if wordFreq > frequency {
frequency = wordFreq
}
}
return frequency
}
// LoadDictionary loads dictionary from given file name. Everytime
// LoadDictionary is called, previously loaded dictionary will be cleard.
func (seg *Segmenter) LoadDictionary(fileName string) error {
seg.dict = &Dictionary{freqMap: make(map[string]float64)}
return seg.dict.loadDictionary(fileName)
}
// LoadUserDictionary loads a user specified dictionary, it must be called
// after LoadDictionary, and it will not clear any previous loaded dictionary,
// instead it will override exist entries.
func (seg *Segmenter) LoadUserDictionary(fileName string) error {
return seg.dict.loadDictionary(fileName)
}
func (seg *Segmenter) dag(runes []rune) map[int][]int {
dag := make(map[int][]int)
n := len(runes)
var frag []rune
var i int
for k := 0; k < n; k++ {
dag[k] = make([]int, 0)
i = k
frag = runes[k : k+1]
for {
freq, ok := seg.dict.Frequency(string(frag))
if !ok {
break
}
if freq > 0.0 {
dag[k] = append(dag[k], i)
}
i++
if i >= n {
break
}
frag = runes[k : i+1]
}
if len(dag[k]) == 0 {
dag[k] = append(dag[k], k)
}
}
return dag
}
type route struct {
frequency float64
index int
}
func (seg *Segmenter) calc(runes []rune) map[int]route {
dag := seg.dag(runes)
n := len(runes)
rs := make(map[int]route)
rs[n] = route{frequency: 0.0, index: 0}
var r route
for idx := n - 1; idx >= 0; idx-- {
for _, i := range dag[idx] {
if freq, ok := seg.dict.Frequency(string(runes[idx : i+1])); ok {
r = route{frequency: math.Log(freq) - seg.dict.logTotal + rs[i+1].frequency, index: i}
} else {
r = route{frequency: math.Log(1.0) - seg.dict.logTotal + rs[i+1].frequency, index: i}
}
if v, ok := rs[idx]; !ok {
rs[idx] = r
} else {
if v.frequency < r.frequency || (v.frequency == r.frequency && v.index < r.index) {
rs[idx] = r
}
}
}
}
return rs
}
type cutFunc func(sentence string) <-chan string
func (seg *Segmenter) cutDAG(sentence string) <-chan string {
result := make(chan string)
go func() {
runes := []rune(sentence)
routes := seg.calc(runes)
var y int
length := len(runes)
var buf []rune
for x := 0; x < length; {
y = routes[x].index + 1
frag := runes[x:y]
if y-x == 1 {
buf = append(buf, frag...)
} else {
if len(buf) > 0 {
bufString := string(buf)
if len(buf) == 1 {
result <- bufString
} else {
if v, ok := seg.dict.Frequency(bufString); !ok || v == 0.0 {
for x := range finalseg.Cut(bufString) {
result <- x
}
} else {
for _, elem := range buf {
result <- string(elem)
}
}
}
buf = make([]rune, 0)
}
result <- string(frag)
}
x = y
}
if len(buf) > 0 {
bufString := string(buf)
if len(buf) == 1 {
result <- bufString
} else {
if v, ok := seg.dict.Frequency(bufString); !ok || v == 0.0 {
for t := range finalseg.Cut(bufString) {
result <- t
}
} else {
for _, elem := range buf {
result <- string(elem)
}
}
}
}
close(result)
}()
return result
}
func (seg *Segmenter) cutDAGNoHMM(sentence string) <-chan string {
result := make(chan string)
go func() {
runes := []rune(sentence)
routes := seg.calc(runes)
var y int
length := len(runes)
var buf []rune
for x := 0; x < length; {
y = routes[x].index + 1
frag := runes[x:y]
if reEng.MatchString(string(frag)) && len(frag) == 1 {
buf = append(buf, frag...)
x = y
continue
}
if len(buf) > 0 {
result <- string(buf)
buf = make([]rune, 0)
}
result <- string(frag)
x = y
}
if len(buf) > 0 {
result <- string(buf)
buf = make([]rune, 0)
}
close(result)
}()
return result
}
// Cut cuts a sentence into words using accurate mode.
// Parameter hmm controls whether to use the Hidden Markov Model.
// Accurate mode attempts to cut the sentence into the most accurate
// segmentations, which is suitable for text analysis.
func (seg *Segmenter) Cut(sentence string, hmm bool) <-chan string {
result := make(chan string)
var cut cutFunc
if hmm {
cut = seg.cutDAG
} else {
cut = seg.cutDAGNoHMM
}
go func() {
for _, block := range util.RegexpSplit(reHanDefault, sentence, -1) {
if len(block) == 0 {
continue
}
if reHanDefault.MatchString(block) {
for x := range cut(block) {
result <- x
}
continue
}
for _, subBlock := range util.RegexpSplit(reSkipDefault, block, -1) {
if reSkipDefault.MatchString(subBlock) {
result <- subBlock
continue
}
for _, r := range subBlock {
result <- string(r)
}
}
}
close(result)
}()
return result
}
func (seg *Segmenter) cutAll(sentence string) <-chan string {
result := make(chan string)
go func() {
runes := []rune(sentence)
dag := seg.dag(runes)
start := -1
ks := make([]int, len(dag))
for k := range dag {
ks[k] = k
}
var l []int
for k := range ks {
l = dag[k]
if len(l) == 1 && k > start {
result <- string(runes[k : l[0]+1])
start = l[0]
continue
}
for _, j := range l {
if j > k {
result <- string(runes[k : j+1])
start = j
}
}
}
close(result)
}()
return result
}
// CutAll cuts a sentence into words using full mode.
// Full mode gets all the possible words from the sentence.
// Fast but not accurate.
func (seg *Segmenter) CutAll(sentence string) <-chan string {
result := make(chan string)
go func() {
for _, block := range util.RegexpSplit(reHanCutAll, sentence, -1) {
if len(block) == 0 {
continue
}
if reHanCutAll.MatchString(block) {
for x := range seg.cutAll(block) {
result <- x
}
continue
}
for _, subBlock := range reSkipCutAll.Split(block, -1) {
result <- subBlock
}
}
close(result)
}()
return result
}
// CutForSearch cuts sentence into words using search engine mode.
// Search engine mode, based on the accurate mode, attempts to cut long words
// into several short words, which can raise the recall rate.
// Suitable for search engines.
func (seg *Segmenter) CutForSearch(sentence string, hmm bool) <-chan string {
result := make(chan string)
go func() {
for word := range seg.Cut(sentence, hmm) {
runes := []rune(word)
for _, increment := range []int{2, 3} {
if len(runes) <= increment {
continue
}
var gram string
for i := 0; i < len(runes)-increment+1; i++ {
gram = string(runes[i : i+increment])
if v, ok := seg.dict.Frequency(gram); ok && v > 0.0 {
result <- gram
}
}
}
result <- word
}
close(result)
}()
return result
}