├── README.md
├── data
├── README.md
└── dictionary.txt
├── dictionary.go
├── go.mod
├── go.sum
├── license.txt
├── segment.go
├── segmenter.go
├── segmenter_test.go
├── server
├── server.go
└── static
│ ├── index.html
│ └── jquery.min.js
├── test_utils.go
├── testdata
├── bailuyuan.txt
├── test_dict1.txt
└── test_dict2.txt
├── token.go
├── tools
├── benchmark.go
├── example.go
└── goroutines.go
├── utils.go
├── utils_test.go
└── vendor
├── github.com
├── adamzy
│ ├── cedar-go
│ │ ├── LICENSE.md
│ │ ├── README.md
│ │ ├── api.go
│ │ ├── cedar.go
│ │ ├── doc.go
│ │ ├── errors.go
│ │ └── io.go
│ └── sego
│ │ ├── README.md
│ │ ├── dictionary.go
│ │ ├── license.txt
│ │ ├── segment.go
│ │ ├── segmenter.go
│ │ ├── test_utils.go
│ │ ├── token.go
│ │ └── utils.go
└── issue9
│ └── assert
│ ├── .editorconfig
│ ├── .gitignore
│ ├── LICENSE
│ ├── README.md
│ ├── assert.go
│ ├── assertion.go
│ ├── doc.go
│ ├── go.mod
│ └── util.go
└── modules.txt
/README.md:
--------------------------------------------------------------------------------
1 | sego
2 | ====
3 |
4 | Go中文分词
5 |
6 | 词典用双数组trie(Double-Array Trie)实现,
7 | 分词器算法为基于词频的最短路径加动态规划。
8 |
9 | 支持普通和搜索引擎两种分词模式,支持用户词典、词性标注,可运行JSON RPC服务。
10 |
11 | 分词速度单线程9MB/s,goroutines并发42MB/s(8核Macbook Pro)。
12 |
13 | # 安装/更新
14 |
15 | ```
16 | go get -u github.com/huichen/sego
17 | ```
18 |
19 | # 使用
20 |
21 |
22 | ```go
23 | package main
24 |
25 | import (
26 | "fmt"
27 | "github.com/huichen/sego"
28 | )
29 |
30 | func main() {
31 | // 载入词典
32 | var segmenter sego.Segmenter
33 | segmenter.LoadDictionary("github.com/huichen/sego/data/dictionary.txt")
34 |
35 | // 分词
36 | text := []byte("中华人民共和国中央人民政府")
37 | segments := segmenter.Segment(text)
38 |
39 | // 处理分词结果
40 | // 支持普通模式和搜索模式两种分词,见代码中SegmentsToString函数的注释。
41 | fmt.Println(sego.SegmentsToString(segments, false))
42 | }
43 | ```
44 |
--------------------------------------------------------------------------------
/data/README.md:
--------------------------------------------------------------------------------
1 | dictionary.txt 词典拷贝自 github.com/fxsjy/jieba
2 |
--------------------------------------------------------------------------------
/dictionary.go:
--------------------------------------------------------------------------------
1 | package sego
2 |
3 | import "github.com/adamzy/cedar-go"
4 |
5 | // Dictionary结构体实现了一个字串前缀树,一个分词可能出现在叶子节点也有可能出现在非叶节点
6 | type Dictionary struct {
7 | trie *cedar.Cedar // Cedar 前缀树
8 | maxTokenLength int // 词典中最长的分词
9 | tokens []Token // 词典中所有的分词,方便遍历
10 | totalFrequency int64 // 词典中所有分词的频率之和
11 | }
12 |
13 | func NewDictionary() *Dictionary {
14 | return &Dictionary{trie: cedar.New()}
15 | }
16 |
17 | // 词典中最长的分词
18 | func (dict *Dictionary) MaxTokenLength() int {
19 | return dict.maxTokenLength
20 | }
21 |
22 | // 词典中分词数目
23 | func (dict *Dictionary) NumTokens() int {
24 | return len(dict.tokens)
25 | }
26 |
27 | // 词典中所有分词的频率之和
28 | func (dict *Dictionary) TotalFrequency() int64 {
29 | return dict.totalFrequency
30 | }
31 |
32 | // 释放资源
33 | func (dict *Dictionary) Close() {
34 | dict.trie = nil
35 | dict.maxTokenLength = 0
36 | dict.tokens = nil
37 | dict.totalFrequency = int64(0)
38 | }
39 |
40 | // 向词典中加入一个分词
41 | func (dict *Dictionary) addToken(token Token) {
42 | bytes := textSliceToBytes(token.text)
43 | _, err := dict.trie.Get(bytes)
44 | if err == nil {
45 | return
46 | }
47 |
48 | dict.trie.Insert(bytes, dict.NumTokens())
49 | dict.tokens = append(dict.tokens, token)
50 | dict.totalFrequency += int64(token.frequency)
51 | if len(token.text) > dict.maxTokenLength {
52 | dict.maxTokenLength = len(token.text)
53 | }
54 | }
55 |
56 | // 在词典中查找和字元组words可以前缀匹配的所有分词
57 | // 返回值为找到的分词数
58 | func (dict *Dictionary) lookupTokens(words []Text, tokens []*Token) (numOfTokens int) {
59 | var id, value int
60 | var err error
61 | for _, word := range words {
62 | id, err = dict.trie.Jump(word, id)
63 | if err != nil {
64 | break
65 | }
66 | value, err = dict.trie.Value(id)
67 | if err == nil {
68 | tokens[numOfTokens] = &dict.tokens[value]
69 | numOfTokens++
70 | }
71 | }
72 | return
73 | }
74 |
--------------------------------------------------------------------------------
/go.mod:
--------------------------------------------------------------------------------
1 | module github.com/huichen/sego
2 |
3 | go 1.16
4 |
5 | require (
6 | github.com/adamzy/cedar-go v0.0.0-20170805034717-80a9c64b256d
7 | github.com/adamzy/sego v0.0.0-20151004184924-5eab9a44f8e8
8 | github.com/issue9/assert v1.4.1
9 | )
10 |
--------------------------------------------------------------------------------
/go.sum:
--------------------------------------------------------------------------------
1 | github.com/adamzy/cedar-go v0.0.0-20170805034717-80a9c64b256d h1:ir/IFJU5xbja5UaBEQLjcvn7aAU01nqU/NUyOBEU+ew=
2 | github.com/adamzy/cedar-go v0.0.0-20170805034717-80a9c64b256d/go.mod h1:PRWNwWq0yifz6XDPZu48aSld8BWwBfr2JKB2bGWiEd4=
3 | github.com/adamzy/sego v0.0.0-20151004184924-5eab9a44f8e8 h1:0RkucRD7zjlMC44X9ni444XpR3vjzyUeHRlViwOwjUw=
4 | github.com/adamzy/sego v0.0.0-20151004184924-5eab9a44f8e8/go.mod h1:KQxo+Xesl2wLJ3yJcX443KaoWzXpbPzU1GNRyE8kNEY=
5 | github.com/issue9/assert v1.4.1 h1:gUtOpMTeaE4JTe9kACma5foOHBvVt1p5XTFrULDwdXI=
6 | github.com/issue9/assert v1.4.1/go.mod h1:Yktk83hAVl1SPSYtd9kjhBizuiBIqUQyj+D5SE2yjVY=
7 |
--------------------------------------------------------------------------------
/license.txt:
--------------------------------------------------------------------------------
1 | Copyright 2013 Hui Chen
2 |
3 | Licensed under the Apache License, Version 2.0 (the "License");
4 | you may not use this file except in compliance with the License.
5 | You may obtain a copy of the License at
6 |
7 | http://www.apache.org/licenses/LICENSE-2.0
8 |
9 | Unless required by applicable law or agreed to in writing, software
10 | distributed under the License is distributed on an "AS IS" BASIS,
11 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 | See the License for the specific language governing permissions and
13 | limitations under the License.
14 |
--------------------------------------------------------------------------------
/segment.go:
--------------------------------------------------------------------------------
1 | package sego
2 |
3 | // 文本中的一个分词
4 | type Segment struct {
5 | // 分词在文本中的起始字节位置
6 | start int
7 |
8 | // 分词在文本中的结束字节位置(不包括该位置)
9 | end int
10 |
11 | // 分词信息
12 | token *Token
13 | }
14 |
15 | // 返回分词在文本中的起始字节位置
16 | func (s *Segment) Start() int {
17 | return s.start
18 | }
19 |
20 | // 返回分词在文本中的结束字节位置(不包括该位置)
21 | func (s *Segment) End() int {
22 | return s.end
23 | }
24 |
25 | // 返回分词信息
26 | func (s *Segment) Token() *Token {
27 | return s.token
28 | }
29 |
--------------------------------------------------------------------------------
/segmenter.go:
--------------------------------------------------------------------------------
1 | //Go中文分词
2 | package sego
3 |
4 | import (
5 | "bufio"
6 | "fmt"
7 | "log"
8 | "math"
9 | "os"
10 | "strconv"
11 | "strings"
12 | "unicode"
13 | "unicode/utf8"
14 | )
15 |
16 | const (
17 | minTokenFrequency = 2 // 仅从字典文件中读取大于等于此频率的分词
18 | )
19 |
20 | // 分词器结构体
21 | type Segmenter struct {
22 | dict *Dictionary
23 | }
24 |
25 | // 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
26 | type jumper struct {
27 | minDistance float32
28 | token *Token
29 | }
30 |
31 | // 返回分词器使用的词典
32 | func (seg *Segmenter) Dictionary() *Dictionary {
33 | return seg.dict
34 | }
35 |
36 | // 从文件中载入词典
37 | //
38 | // 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
39 | // "用户词典.txt,通用词典.txt"
40 | // 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。
41 | //
42 | // 词典的格式为(每个分词一行):
43 | // 分词文本 频率 词性
44 | func (seg *Segmenter) LoadDictionary(files string) {
45 | seg.dict = NewDictionary()
46 | for _, file := range strings.Split(files, ",") {
47 | log.Printf("载入sego词典 %s", file)
48 | dictFile, err := os.Open(file)
49 | defer dictFile.Close()
50 | if err != nil {
51 | log.Fatalf("无法载入字典文件 \"%s\" \n", file)
52 | }
53 |
54 | reader := bufio.NewReader(dictFile)
55 | var text string
56 | var freqText string
57 | var frequency int
58 | var pos string
59 |
60 | // 逐行读入分词
61 | for {
62 | size, _ := fmt.Fscanln(reader, &text, &freqText, &pos)
63 |
64 | if size == 0 {
65 | // 文件结束
66 | break
67 | } else if size < 2 {
68 | // 无效行
69 | continue
70 | } else if size == 2 {
71 | // 没有词性标注时设为空字符串
72 | pos = ""
73 | }
74 |
75 | // 解析词频
76 | var err error
77 | frequency, err = strconv.Atoi(freqText)
78 | if err != nil {
79 | continue
80 | }
81 |
82 | // 过滤频率太小的词
83 | if frequency < minTokenFrequency {
84 | continue
85 | }
86 |
87 | // 将分词添加到字典中
88 | words := splitTextToWords([]byte(text))
89 | token := Token{text: words, frequency: frequency, pos: pos}
90 | seg.dict.addToken(token)
91 | }
92 | }
93 |
94 | // 计算每个分词的路径值,路径值含义见Token结构体的注释
95 | logTotalFrequency := float32(math.Log2(float64(seg.dict.totalFrequency)))
96 | for i := range seg.dict.tokens {
97 | token := &seg.dict.tokens[i]
98 | token.distance = logTotalFrequency - float32(math.Log2(float64(token.frequency)))
99 | }
100 |
101 | // 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。
102 | for i := range seg.dict.tokens {
103 | token := &seg.dict.tokens[i]
104 | segments := seg.segmentWords(token.text, true)
105 |
106 | // 计算需要添加的子分词数目
107 | numTokensToAdd := 0
108 | for iToken := 0; iToken < len(segments); iToken++ {
109 | if len(segments[iToken].token.text) > 0 {
110 | numTokensToAdd++
111 | }
112 | }
113 | token.segments = make([]*Segment, numTokensToAdd)
114 |
115 | // 添加子分词
116 | iSegmentsToAdd := 0
117 | for iToken := 0; iToken < len(segments); iToken++ {
118 | if len(segments[iToken].token.text) > 0 {
119 | token.segments[iSegmentsToAdd] = &segments[iToken]
120 | iSegmentsToAdd++
121 | }
122 | }
123 | }
124 |
125 | log.Println("sego词典载入完毕")
126 | }
127 |
128 | // 对文本分词
129 | //
130 | // 输入参数:
131 | // bytes UTF8文本的字节数组
132 | //
133 | // 输出:
134 | // []Segment 划分的分词
135 | func (seg *Segmenter) Segment(bytes []byte) []Segment {
136 | return seg.internalSegment(bytes, false)
137 | }
138 |
139 | func (seg *Segmenter) InternalSegment(bytes []byte, searchMode bool) []Segment {
140 | return seg.internalSegment(bytes, searchMode)
141 | }
142 |
143 | // 释放资源
144 | func (seg *Segmenter) Close() {
145 | if seg.dict != nil {
146 | seg.dict.Close()
147 | }
148 | }
149 |
150 | func (seg *Segmenter) internalSegment(bytes []byte, searchMode bool) []Segment {
151 | // 处理特殊情况
152 | if len(bytes) == 0 {
153 | return []Segment{}
154 | }
155 |
156 | // 划分字元
157 | text := splitTextToWords(bytes)
158 |
159 | return seg.segmentWords(text, searchMode)
160 | }
161 |
162 | func (seg *Segmenter) segmentWords(text []Text, searchMode bool) []Segment {
163 | // 搜索模式下该分词已无继续划分可能的情况
164 | if searchMode && len(text) == 1 {
165 | return []Segment{}
166 | }
167 |
168 | // 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,
169 | // 以及从文本段开始到该字元的最短路径值
170 | jumpers := make([]jumper, len(text))
171 |
172 | tokens := make([]*Token, seg.dict.maxTokenLength)
173 | for current := 0; current < len(text); current++ {
174 | // 找到前一个字元处的最短路径,以便计算后续路径值
175 | var baseDistance float32
176 | if current == 0 {
177 | // 当本字元在文本首部时,基础距离应该是零
178 | baseDistance = 0
179 | } else {
180 | baseDistance = jumpers[current-1].minDistance
181 | }
182 |
183 | // 寻找所有以当前字元开头的分词
184 | numTokens := seg.dict.lookupTokens(
185 | text[current:minInt(current+seg.dict.maxTokenLength, len(text))], tokens)
186 |
187 | // 对所有可能的分词,更新分词结束字元处的跳转信息
188 | for iToken := 0; iToken < numTokens; iToken++ {
189 | location := current + len(tokens[iToken].text) - 1
190 | if !searchMode || current != 0 || location != len(text)-1 {
191 | updateJumper(&jumpers[location], baseDistance, tokens[iToken])
192 | }
193 | }
194 |
195 | // 当前字元没有对应分词时补加一个伪分词
196 | if numTokens == 0 || len(tokens[0].text) > 1 {
197 | updateJumper(&jumpers[current], baseDistance,
198 | &Token{text: []Text{text[current]}, frequency: 1, distance: 32, pos: "x"})
199 | }
200 | }
201 |
202 | // 从后向前扫描第一遍得到需要添加的分词数目
203 | numSeg := 0
204 | for index := len(text) - 1; index >= 0; {
205 | location := index - len(jumpers[index].token.text) + 1
206 | numSeg++
207 | index = location - 1
208 | }
209 |
210 | // 从后向前扫描第二遍添加分词到最终结果
211 | outputSegments := make([]Segment, numSeg)
212 | for index := len(text) - 1; index >= 0; {
213 | location := index - len(jumpers[index].token.text) + 1
214 | numSeg--
215 | outputSegments[numSeg].token = jumpers[index].token
216 | index = location - 1
217 | }
218 |
219 | // 计算各个分词的字节位置
220 | bytePosition := 0
221 | for iSeg := 0; iSeg < len(outputSegments); iSeg++ {
222 | outputSegments[iSeg].start = bytePosition
223 | bytePosition += textSliceByteLength(outputSegments[iSeg].token.text)
224 | outputSegments[iSeg].end = bytePosition
225 | }
226 | return outputSegments
227 | }
228 |
229 | // 更新跳转信息:
230 | // 1. 当该位置从未被访问过时(jumper.minDistance为零的情况),或者
231 | // 2. 当该位置的当前最短路径大于新的最短路径时
232 | // 将当前位置的最短路径值更新为baseDistance加上新分词的概率
233 | func updateJumper(jumper *jumper, baseDistance float32, token *Token) {
234 | newDistance := baseDistance + token.distance
235 | if jumper.minDistance == 0 || jumper.minDistance > newDistance {
236 | jumper.minDistance = newDistance
237 | jumper.token = token
238 | }
239 | }
240 |
241 | // 取两整数较小值
242 | func minInt(a, b int) int {
243 | if a > b {
244 | return b
245 | }
246 | return a
247 | }
248 |
249 | // 取两整数较大值
250 | func maxInt(a, b int) int {
251 | if a > b {
252 | return a
253 | }
254 | return b
255 | }
256 |
257 | // 将文本划分成字元
258 | func splitTextToWords(text Text) []Text {
259 | output := make([]Text, 0, len(text)/3)
260 | current := 0
261 | inAlphanumeric := true
262 | alphanumericStart := 0
263 | for current < len(text) {
264 | r, size := utf8.DecodeRune(text[current:])
265 | if size <= 2 && (unicode.IsLetter(r) || unicode.IsNumber(r)) {
266 | // 当前是拉丁字母或数字(非中日韩文字)
267 | if !inAlphanumeric {
268 | alphanumericStart = current
269 | inAlphanumeric = true
270 | }
271 | } else {
272 | if inAlphanumeric {
273 | inAlphanumeric = false
274 | if current != 0 {
275 | output = append(output, toLower(text[alphanumericStart:current]))
276 | }
277 | }
278 | output = append(output, text[current:current+size])
279 | }
280 | current += size
281 | }
282 |
283 | // 处理最后一个字元是英文的情况
284 | if inAlphanumeric {
285 | if current != 0 {
286 | output = append(output, toLower(text[alphanumericStart:current]))
287 | }
288 | }
289 |
290 | return output
291 | }
292 |
293 | // 将英文词转化为小写
294 | func toLower(text []byte) []byte {
295 | output := make([]byte, len(text))
296 | for i, t := range text {
297 | if t >= 'A' && t <= 'Z' {
298 | output[i] = t - 'A' + 'a'
299 | } else {
300 | output[i] = t
301 | }
302 | }
303 | return output
304 | }
305 |
--------------------------------------------------------------------------------
/segmenter_test.go:
--------------------------------------------------------------------------------
1 | package sego
2 |
3 | import (
4 | "testing"
5 | )
6 |
7 | var (
8 | prodSeg = Segmenter{}
9 | )
10 |
11 | func TestSplit(t *testing.T) {
12 | expect(t, "中/国/有/十/三/亿/人/口/",
13 | bytesToString(splitTextToWords([]byte(
14 | "中国有十三亿人口"))))
15 |
16 | expect(t, "github/ /is/ /a/ /web/-/based/ /hosting/ /service/,/ /for/ /software/ /development/ /projects/./",
17 | bytesToString(splitTextToWords([]byte(
18 | "GitHub is a web-based hosting service, for software development projects."))))
19 |
20 | expect(t, "中/国/雅/虎/yahoo/!/ /china/致/力/于/,/领/先/的/公/益/民/生/门/户/网/站/。/",
21 | bytesToString(splitTextToWords([]byte(
22 | "中国雅虎Yahoo! China致力于,领先的公益民生门户网站。"))))
23 |
24 | expect(t, "こ/ん/に/ち/は/", bytesToString(splitTextToWords([]byte("こんにちは"))))
25 |
26 | expect(t, "안/녕/하/세/요/", bytesToString(splitTextToWords([]byte("안녕하세요"))))
27 |
28 | expect(t, "Я/ /тоже/ /рада/ /Вас/ /видеть/", bytesToString(splitTextToWords([]byte("Я тоже рада Вас видеть"))))
29 |
30 | expect(t, "¿/cómo/ /van/ /las/ /cosas/", bytesToString(splitTextToWords([]byte("¿Cómo van las cosas"))))
31 |
32 | expect(t, "wie/ /geht/ /es/ /ihnen/", bytesToString(splitTextToWords([]byte("Wie geht es Ihnen"))))
33 |
34 | expect(t, "je/ /suis/ /enchanté/ /de/ /cette/ /pièce/",
35 | bytesToString(splitTextToWords([]byte("Je suis enchanté de cette pièce"))))
36 | }
37 |
38 | func TestSegment(t *testing.T) {
39 | var seg Segmenter
40 | seg.LoadDictionary("testdata/test_dict1.txt,testdata/test_dict2.txt")
41 | expect(t, "12", seg.dict.NumTokens())
42 | segments := seg.Segment([]byte("中国有十三亿人口"))
43 | expect(t, "中国/ 有/p3 十三亿/ 人口/p12 ", SegmentsToString(segments, false))
44 | expect(t, "4", len(segments))
45 | expect(t, "0", segments[0].start)
46 | expect(t, "6", segments[0].end)
47 | expect(t, "6", segments[1].start)
48 | expect(t, "9", segments[1].end)
49 | expect(t, "9", segments[2].start)
50 | expect(t, "18", segments[2].end)
51 | expect(t, "18", segments[3].start)
52 | expect(t, "24", segments[3].end)
53 | }
54 |
55 | func TestLargeDictionary(t *testing.T) {
56 | prodSeg.LoadDictionary("data/dictionary.txt")
57 | expect(t, "中国/ns 人口/n ", SegmentsToString(prodSeg.Segment(
58 | []byte("中国人口")), false))
59 |
60 | expect(t, "中国/ns 人口/n ", SegmentsToString(prodSeg.internalSegment(
61 | []byte("中国人口"), false), false))
62 |
63 | expect(t, "中国/ns 人口/n ", SegmentsToString(prodSeg.internalSegment(
64 | []byte("中国人口"), true), false))
65 |
66 | expect(t, "中华人民共和国/ns 中央人民政府/nt ", SegmentsToString(prodSeg.internalSegment(
67 | []byte("中华人民共和国中央人民政府"), true), false))
68 |
69 | expect(t, "中华人民共和国中央人民政府/nt ", SegmentsToString(prodSeg.internalSegment(
70 | []byte("中华人民共和国中央人民政府"), false), false))
71 |
72 | expect(t, "中华/nz 人民/n 共和/nz 国/n 共和国/ns 人民共和国/nt 中华人民共和国/ns 中央/n 人民/n 政府/n 人民政府/nt 中央人民政府/nt 中华人民共和国中央人民政府/nt ", SegmentsToString(prodSeg.Segment(
73 | []byte("中华人民共和国中央人民政府")), true))
74 | }
75 |
--------------------------------------------------------------------------------
/server/server.go:
--------------------------------------------------------------------------------
1 | /*
2 |
3 | sego分词服务器同时提供了两种模式:
4 |
5 | "/" 分词演示网页
6 | "/json" JSON格式的RPC服务
7 | 输入:
8 | POST或GET模式输入text参数
9 | 输出JSON格式:
10 | {
11 | segments:[
12 | {"text":"服务器", "pos":"n"},
13 | {"text":"指令", "pos":"n"},
14 | ...
15 | ]
16 | }
17 |
18 |
19 | 测试服务器见 http://sego.weiboglass.com
20 |
21 | */
22 |
23 | package main
24 |
25 | import (
26 | "encoding/json"
27 | "flag"
28 | "fmt"
29 | "github.com/huichen/sego"
30 | "io"
31 | "log"
32 | "net/http"
33 | "runtime"
34 | )
35 |
36 | var (
37 | host = flag.String("host", "", "HTTP服务器主机名")
38 | port = flag.Int("port", 8080, "HTTP服务器端口")
39 | dict = flag.String("dict", "../data/dictionary.txt", "词典文件")
40 | staticFolder = flag.String("static_folder", "static", "静态页面存放的目录")
41 | segmenter = sego.Segmenter{}
42 | )
43 |
44 | type JsonResponse struct {
45 | Segments []*Segment `json:"segments"`
46 | }
47 |
48 | type Segment struct {
49 | Text string `json:"text"`
50 | Pos string `json:"pos"`
51 | }
52 |
53 | func JsonRpcServer(w http.ResponseWriter, req *http.Request) {
54 | // 得到要分词的文本
55 | text := req.URL.Query().Get("text")
56 | if text == "" {
57 | text = req.PostFormValue("text")
58 | }
59 |
60 | // 分词
61 | segments := segmenter.Segment([]byte(text))
62 |
63 | // 整理为输出格式
64 | ss := []*Segment{}
65 | for _, segment := range segments {
66 | ss = append(ss, &Segment{Text: segment.Token().Text(), Pos: segment.Token().Pos()})
67 | }
68 | response, _ := json.Marshal(&JsonResponse{Segments: ss})
69 |
70 | w.Header().Set("Content-Type", "application/json")
71 | io.WriteString(w, string(response))
72 | }
73 |
74 | func main() {
75 | flag.Parse()
76 |
77 | // 将线程数设置为CPU数
78 | runtime.GOMAXPROCS(runtime.NumCPU())
79 |
80 | // 初始化分词器
81 | segmenter.LoadDictionary(*dict)
82 |
83 | http.HandleFunc("/json", JsonRpcServer)
84 | http.Handle("/", http.FileServer(http.Dir(*staticFolder)))
85 | log.Print("服务器启动")
86 | http.ListenAndServe(fmt.Sprintf("%s:%d", *host, *port), nil)
87 | }
88 |
--------------------------------------------------------------------------------
/server/static/index.html:
--------------------------------------------------------------------------------
1 |
2 |
3 |
sego中文分词演示
4 |
5 |
8 |
9 |
10 |
48 |
49 |
50 |
51 | sego中文分词演示
52 |
53 |
54 |
61 |
62 |
63 |
64 |
65 |
66 |
67 |
68 |
69 |
70 |
71 |
72 |
73 |
74 |
75 |
--------------------------------------------------------------------------------
/server/static/jquery.min.js:
--------------------------------------------------------------------------------
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