ukui-search/libchinese-segmentation/cppjieba/TextRankExtractor.hpp

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/*
* The MIT License (MIT)
*
* Copyright (C) 2013 Yanyi Wu
* Copyright (C) 2023, KylinSoft Co., Ltd.
*
* Permission is hereby granted, free of charge, to any person obtaining a
* copy of this software and associated documentation files (the "Software"),
* to deal in the Software without restriction, including without limitation
* the rights to use, copy, modify, merge, publish, distribute, sublicense,
* and/or sell copies of the Software, and to permit persons to whom the
* Software is furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be
* included in all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
* OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
* THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR
* OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
* ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
* OTHER DEALINGS IN THE SOFTWARE.
*
*/
#include <cmath>
#include "Jieba.hpp"
namespace cppjieba {
using namespace limonp;
using namespace std;
class TextRankExtractor {
public:
typedef struct _Word {
string word;
vector<size_t> offsets;
double weight;
} Word; // struct Word
private:
typedef std::map<string, Word> WordMap;
class WordGraph {
private:
typedef double Score;
typedef string Node;
typedef std::set<Node> NodeSet;
typedef std::map<Node, double> Edges;
typedef std::map<Node, Edges> Graph;
//typedef std::unordered_map<Node,double> Edges;
//typedef std::unordered_map<Node,Edges> Graph;
double d;
Graph graph;
NodeSet nodeSet;
public:
WordGraph(): d(0.85) {};
WordGraph(double in_d): d(in_d) {};
void addEdge(Node start, Node end, double weight) {
Edges temp;
Edges::iterator gotEdges;
nodeSet.insert(start);
nodeSet.insert(end);
graph[start][end] += weight;
graph[end][start] += weight;
}
void rank(WordMap &ws, size_t rankTime = 10) {
WordMap outSum;
Score wsdef, min_rank, max_rank;
if (graph.size() == 0) {
return;
}
wsdef = 1.0 / graph.size();
for (Graph::iterator edges = graph.begin(); edges != graph.end(); ++edges) {
// edges->first start节点edge->first end节点edge->second 权重
ws[edges->first].word = edges->first;
ws[edges->first].weight = wsdef;
outSum[edges->first].weight = 0;
for (Edges::iterator edge = edges->second.begin(); edge != edges->second.end(); ++edge) {
outSum[edges->first].weight += edge->second;
}
}
//sort(nodeSet.begin(),nodeSet.end()); 是否需要排序?
for (size_t i = 0; i < rankTime; i++) {
for (NodeSet::iterator node = nodeSet.begin(); node != nodeSet.end(); node++) {
double s = 0;
for (Edges::iterator edge = graph[*node].begin(); edge != graph[*node].end(); edge++)
// edge->first end节点edge->second 权重
{
s += edge->second / outSum[edge->first].weight * ws[edge->first].weight;
}
ws[*node].weight = (1 - d) + d * s;
}
}
min_rank = max_rank = ws.begin()->second.weight;
for (WordMap::iterator i = ws.begin(); i != ws.end(); i ++) {
if (i->second.weight < min_rank) {
min_rank = i->second.weight;
}
if (i->second.weight > max_rank) {
max_rank = i->second.weight;
}
}
for (WordMap::iterator i = ws.begin(); i != ws.end(); i ++) {
ws[i->first].weight = (i->second.weight - min_rank / 10.0) / (max_rank - min_rank / 10.0);
}
}
};
public:
TextRankExtractor(const DictTrie* dictTrie,
const HMMModel* model,
const string& stopWordPath)
: segment_(dictTrie, model) {
LoadStopWordDict(stopWordPath);
}
TextRankExtractor(const Jieba& jieba, const string& stopWordPath) : segment_(jieba.GetDictTrie(), jieba.GetHMMModel()) {
LoadStopWordDict(stopWordPath);
}
~TextRankExtractor() {
}
void Extract(const string& sentence, vector<string>& keywords, size_t topN) const {
vector<Word> topWords;
Extract(sentence, topWords, topN);
for (size_t i = 0; i < topWords.size(); i++) {
keywords.push_back(topWords[i].word);
}
}
void Extract(const string& sentence, vector<pair<string, double> >& keywords, size_t topN) const {
vector<Word> topWords;
Extract(sentence, topWords, topN);
for (size_t i = 0; i < topWords.size(); i++) {
keywords.push_back(pair<string, double>(topWords[i].word, topWords[i].weight));
}
}
void Extract(const string& sentence, vector<Word>& keywords, size_t topN, size_t span = 5, size_t rankTime = 10) const {
vector<string> words;
segment_.CutToStr(sentence, words);
TextRankExtractor::WordGraph graph;
WordMap wordmap;
size_t offset = 0;
for (size_t i = 0; i < words.size(); i++) {
size_t t = offset;
offset += words[i].size();
if (IsSingleWord(words[i]) || stopWords_.find(words[i]) != stopWords_.end()) {
continue;
}
for (size_t j = i + 1, skip = 0; j < i + span + skip && j < words.size(); j++) {
if (IsSingleWord(words[j]) || stopWords_.find(words[j]) != stopWords_.end()) {
skip++;
continue;
}
graph.addEdge(words[i], words[j], 1);
}
wordmap[words[i]].offsets.push_back(t);
}
if (offset != sentence.size()) {
XLOG(ERROR) << "words illegal";
return;
}
graph.rank(wordmap, rankTime);
keywords.clear();
keywords.reserve(wordmap.size());
for (WordMap::iterator itr = wordmap.begin(); itr != wordmap.end(); ++itr) {
keywords.push_back(itr->second);
}
topN = min(topN, keywords.size());
partial_sort(keywords.begin(), keywords.begin() + topN, keywords.end(), Compare);
keywords.resize(topN);
}
private:
void LoadStopWordDict(const string& filePath) {
ifstream ifs(filePath.c_str());
XCHECK(ifs.is_open()) << "open " << filePath << " failed";
string line ;
while (getline(ifs, line)) {
stopWords_.insert(line);
}
assert(stopWords_.size());
}
static bool Compare(const Word &x, const Word &y) {
return x.weight > y.weight;
}
MixSegment segment_;
unordered_set<string> stopWords_;
}; // class TextRankExtractor
inline ostream& operator << (ostream& os, const TextRankExtractor::Word& word) {
return os << "{\"word\": \"" << word.word << "\", \"offset\": " << word.offsets << ", \"weight\": " << word.weight <<
"}";
}
} // namespace cppjieba