1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
|
/*
* Copyright (C) 2012 Canonical, Ltd.
*
* Authors:
* Jussi Pakkanen <jussi.pakkanen@canonical.com>
*
* This library is free software; you can redistribute it and/or modify it under
* the terms of version 3 of the GNU Lesser General Public License as published
* by the Free Software Foundation.
*
* This library is distributed in the hope that it will be useful, but WITHOUT
* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
* FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more
* details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
/*
* This file implements a fast Levenshtein matcher for a dictionary of
* words. It is a re-implementation of code placed in the public domain
* here:
*
* http://stevehanov.ca/blog/index.php?id=114
*/
#include <stdio.h>
#include <cassert>
#include <map>
#include <vector>
#include "LevenshteinIndex.hh"
#include "ErrorValues.hh"
#include "Word.hh"
#include "ErrorMatrix.hh"
#include "Trie.hh"
#ifdef HAS_SPARSE_HASH
#include <google/sparse_hash_map>
using google::sparse_hash_map;
#define hashmap sparse_hash_map
#else
#include <unordered_map>
#define hashmap unordered_map
#endif
COL_NAMESPACE_START
using namespace std;
typedef vector<pair<Letter, TrieNode*> > ChildList;
typedef ChildList::iterator ChildListIter;
typedef ChildList::const_iterator ChildListConstIter;
typedef hashmap<WordID, size_t> WordCount;
struct LevenshteinIndexPrivate {
WordCount wordCounts; // How many times the word has been added to this index.
size_t maxCount; // How many times the most common word has been added.
size_t numNodes;
size_t numWords; // How many words are in this index in total.
size_t longestWordLength; // Longest word that has been added. Same as tree depth.
Trie trie;
};
LevenshteinIndex::LevenshteinIndex() {
p = new LevenshteinIndexPrivate();
p->maxCount = 0;
p->longestWordLength = 0;
}
LevenshteinIndex::~LevenshteinIndex() {
delete p;
}
int LevenshteinIndex::getDefaultError() {
return ErrorValues::getDefaultError();
}
void LevenshteinIndex::insertWord(const Word &word, const WordID wordID) {
if(word.length() == 0)
return;
auto it = p->wordCounts.find(wordID);
size_t newCount;
if(it != p->wordCounts.end()) {
newCount = p->wordCounts[wordID] + 1;
} else {
newCount = 1;
}
p->trie.insertWord(word, wordID);
p->wordCounts[wordID] = newCount;
if(word.length() > p->longestWordLength)
p->longestWordLength = word.length();
if(p->maxCount < newCount)
p->maxCount = newCount;
return;
}
bool LevenshteinIndex::hasWord(const Word &word) const {
return p->trie.hasWord(word);
}
void LevenshteinIndex::findWords(const Word &query, const ErrorValues &e, const int maxError, IndexMatches &matches) const {
TrieOffset root;
TrieOffset sibling;
ErrorMatrix em(p->longestWordLength+1, query.length()+1,
e.getDeletionError(), e.getStartInsertionError(query.length()));
assert(em.get(0, 0) == 0);
if(query.length() > 0)
assert(em.get(0, 1) == e.getInsertionError());
root = p->trie.getRoot();
sibling = p->trie.getSiblingList(root);
while(sibling != 0) {
Letter l = p->trie.getLetter(sibling);
TrieOffset nextNode = p->trie.getChild(sibling);
searchRecursive(query, nextNode, e, l, (Letter)0, 1, em, matches, maxError);
sibling = p->trie.getNextSibling(sibling);
}
matches.sort();
}
int LevenshteinIndex::findOptimalError(const Letter letter, const Letter previousLetter, const Word &query,
const size_t i, const size_t depth, const ErrorMatrix &em, const ErrorValues &e) const {
int insertError = em.get(depth, i-1) + e.getInsertionError();
int deleteError;
if(i >= query.length())
deleteError = em.get(depth-1, i) + e.getEndDeletionError();
else
deleteError = em.get(depth-1, i) + e.getDeletionError();
int substituteError = em.get(depth-1, i-1) + e.getSubstituteError(query.text[i-1], letter);
int transposeError;
if(i > 1 && query.text[i - 1] == previousLetter && query.text[i - 2] == letter) {
transposeError = em.get(depth-2, i-2) + e.getTransposeError();
} else {
transposeError = insertError + 10000; // Ensures this will not be chosen.
}
return min(insertError, min(deleteError, min(substituteError, transposeError)));
}
void LevenshteinIndex::searchRecursive(const Word &query, TrieOffset node, const ErrorValues &e,
const Letter letter, const Letter previousLetter, const size_t depth, ErrorMatrix &em,
IndexMatches &matches, const int maxError) const {
for(size_t i = 1; i < query.length()+1; i++) {
int minError = findOptimalError(letter, previousLetter, query, i, depth, em, e);
em.set(depth, i, minError);
}
// Error row evaluated. Now check if a word was found and continue recursively.
if(em.totalError(depth) <= maxError && p->trie.getWordID(node) != INVALID_WORDID) {
matches.addMatch(query, p->trie.getWordID(node), em.totalError(depth));
}
if(em.minError(depth) <= maxError) {
TrieOffset sibling = p->trie.getSiblingList(node);
while(sibling != 0) {
Letter l = p->trie.getLetter(sibling);
TrieOffset nextNode = p->trie.getChild(sibling);
searchRecursive(query, nextNode, e, l, letter, depth+1, em, matches, maxError);
sibling = p->trie.getNextSibling(sibling);
}
}
}
size_t LevenshteinIndex::wordCount(const WordID queryID) const {
auto i = p->wordCounts.find(queryID);
if(i == p->wordCounts.end())
return 0;
return i->second;
}
size_t LevenshteinIndex::maxCount() const {
return p->maxCount;
}
size_t LevenshteinIndex::numNodes() const {
return p->trie.numNodes();
}
size_t LevenshteinIndex::numWords() const {
return p->trie.numWords();
}
COL_NAMESPACE_END
|