Python容错的前缀树实现中文纠错

介绍

本文使用 Python 实现了前缀树,并且支持编辑距离容错的查询。文中的前缀树只存储了三个分词,格式为 (分词字符串,频率) ,如:('中海晋西园', 2)、('中海西园', 24)、('中南海', 4),可以换成自己的文件进行数据的替换。在查询的时候要指定一个字符串和最大的容错编辑距离。

实现

class Word:
    def __init__(self, word, freq):
        self.word = word
        self.freq = freq

class Trie:
    def __init__(self):
        self.root = LetterNode('')
        self.START = 3

    def insert(self, word, freq):
        self.root.insert(word, freq, 0)

    def findAll(self, query, maxDistance):
        suggestions = self.root.recommend(query, maxDistance, self.START)
        return sorted(set(suggestions), key=lambda x: x.freq)


class LetterNode:
    def __init__(self, char):
        self.REMOVE = -1
        self.ADD = 1
        self.SAME = 0
        self.CHANGE = 2
        self.START = 3
        self.pointers = []
        self.char = char
        self.word = None

    def charIs(self, c):
        return self.char == c

    def insert(self, word, freq, depth):
        if ' ' in word:
            word = [i for i in word.split(' ')]
        if depth < len(word):
            c = word[depth].lower()
            for next in self.pointers:
                if next.charIs(c):
                    return next.insert(word, freq, depth + 1)
            nextNode = LetterNode(c)
            self.pointers.append(nextNode)
            return nextNode.insert(word, freq, depth + 1)
        else:
            self.word = Word(word, freq)

    def recommend(self, query, movesLeft, lastAction):
        suggestions = []
        length = len(query)

        if length >= 0 and movesLeft - length >= 0 and self.word:
            suggestions.append(self.word)

        if movesLeft == 0 and length > 0:
            for next in self.pointers:
                if next.charIs(query[0]):
                    suggestions += next.recommend(query[1:], movesLeft, self.SAME)
                    break

        elif movesLeft > 0:
            for next in self.pointers:
                if length > 0:
                    if next.charIs(query[0]):
                        suggestions += next.recommend(query[1:], movesLeft, self.SAME)
                    else:
                        suggestions += next.recommend(query[1:], movesLeft - 1, self.CHANGE)
                        if lastAction != self.CHANGE and lastAction != self.REMOVE:
                            suggestions += next.recommend(query, movesLeft - 1, self.ADD)
                        if lastAction != self.ADD and lastAction != self.CHANGE:
                            if length > 1 and next.charIs(query[1]):
                                suggestions += next.recommend(query[2:], movesLeft - 1, self.REMOVE)
                            elif length > 2 and next.charIs(query[2]) and movesLeft == 2:
                                suggestions += next.recommend(query[3:], movesLeft - 2, self.REMOVE)
                else:
                    if lastAction != self.CHANGE and lastAction != self.REMOVE:
                        suggestions += next.recommend(query, movesLeft - 1, self.ADD)
        return suggestions



def buildTrieFromFile():
    trie = Trie()
    rows = [('中海晋西园', 2),('中海西园', 24),('中南海', 4)]
    for row in rows:
        trie.insert(row[0], int(row[1]))
    return trie


def suggestor(trie, s, maxDistance):
    if ' ' in s:
        s = [x for x in s.split(' ')]
    suggestions = trie.findAll(s, maxDistance)
    return [str(x.word) for x in suggestions]


if __name__ == "__main__":
    trie = buildTrieFromFile()
    r = suggestor(trie, '中海晋西园', 1)
    print(r)

分析

结果打印:
['中海晋西园', '中海西园']

可以看出“中海晋西园”是和输入完全相同的字符串,编辑距离为 0 ,所以符合最大编辑距离为 1 的要求,直接返回。

“中海西园”是“中海晋西园”去掉“晋”字之后的结果,编辑距离为 1, 所以符合最大编辑距离为 1 的要求,直接返回。

另外,“中南海”和“中海晋西园”的编辑距离为 4 ,不符合最大编辑距离为 1 的要求,所以结果中没有出现。

参考

https://github.com/leoRoss/AutoCorrectTrie

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