117 lines
4.3 KiB
C
117 lines
4.3 KiB
C
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/*
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* Copyright (C) 2020, KylinSoft Co., Ltd.
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*
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* This program is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program. If not, see <https://www.gnu.org/licenses/>.
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*
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*
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*/
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#ifndef CHINESESEGMENTATION_H
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#define CHINESESEGMENTATION_H
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#include <QString>
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#include "libchinese-segmentation_global.h"
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#include "common-struct.h"
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class ChineseSegmentationPrivate;
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class CHINESESEGMENTATION_EXPORT ChineseSegmentation {
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public:
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static ChineseSegmentation *getInstance();
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/**
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* @brief ChineseSegmentation::callSegment
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* 调用extractor进行关键词提取，先使用Mix方式初步分词，再使用Idf词典进行关键词提取，只包含两字以上关键词
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*
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* @param sentence 要提取关键词的句子
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* @return vector<KeyWord> 存放提取后关键词的信息的容器
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*/
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vector<KeyWord> callSegment(const string &sentence);
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vector<KeyWord> callSegment(QString &sentence);
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/**
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* @brief ChineseSegmentation::callMixSegmentCutStr
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* 使用Mix方法进行分词，即先使用最大概率法MP初步分词，再用隐式马尔科夫模型HMM进一步分词，可以准确切出词典已有词和未登录词，结果比较准确
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*
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* @param sentence 要分词的句子
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* @return vector<string> 只存放分词后每个词的内容的容器
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*/
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vector<string> callMixSegmentCutStr(const string& sentence);
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/**
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* @brief ChineseSegmentation::callMixSegmentCutWord
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* 和callMixSegmentCutStr功能相同
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* @param sentence 要分词的句子
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* @return vector<Word> 存放分词后每个词所有信息的容器
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*/
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vector<Word> callMixSegmentCutWord(const string& str);
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/**
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* @brief ChineseSegmentation::lookUpTagOfWord
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* 查询word的词性
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* @param word 要查询词性的词
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* @return string word的词性
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*/
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string lookUpTagOfWord(const string& word);
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/**
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* @brief ChineseSegmentation::getTagOfWordsInSentence
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* 使用Mix分词后获取每个词的词性
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* @param sentence 要分词的句子
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* @return vector<pair<string, string>> 分词后的每个词的内容(firsr)和其对应的词性(second)
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*/
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vector<pair<string, string>> getTagOfWordsInSentence(const string &sentence);
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/**
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* @brief ChineseSegmentation::callFullSegment
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* 使用Full进行分词，Full会切出字典里所有的词。
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* @param sentence 要分词的句子
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* @return vector<Word> 存放分词后每个词所有信息的容器
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*/
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vector<Word> callFullSegment(const string& sentence);
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/**
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* @brief ChineseSegmentation::callQuerySegment
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* 使用Query进行分词，即先使用Mix，对于长词再用Full，结果最精确，但词的数量也最大
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* @param sentence 要分词的句子
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* @return vector<Word> 存放分词后每个词所有信息的容器
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*/
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vector<Word> callQuerySegment(const string& sentence);
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/**
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* @brief ChineseSegmentation::callHMMSegment
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* 使用隐式马尔科夫模型HMM进行分词
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* @param sentence 要分词的句子
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* @return vector<Word> 存放分词后每个词所有信息的容器
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*/
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vector<Word> callHMMSegment(const string& sentence);
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/**
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* @brief ChineseSegmentation::callMPSegment
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* 使用最大概率法MP进行分词
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* @param sentence 要分词的句子
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* @return vector<Word> 存放分词后每个词所有信息的容器
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*/
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vector<Word> callMPSegment(const string& sentence);
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private:
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explicit ChineseSegmentation();
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~ChineseSegmentation() = default;
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ChineseSegmentation(const ChineseSegmentation&) = delete;
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ChineseSegmentation& operator =(const ChineseSegmentation&) = delete;
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private:
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ChineseSegmentationPrivate *d = nullptr;
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};
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#endif // CHINESESEGMENTATION_H
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