【python 走进NLP】英文敏感词过滤算法改进版本

中文DFA算法过滤敏感词改进版本

# 中文DFA算法过滤敏感词改进版本
class Chinese_DFAFilter():
    def __init__(self):
        self.keyword_chains = {}
        self.delimit = '\x00'

    def add(self, keyword):
        keyword = keyword.lower()
        chars = keyword.strip()
        if not chars:
            return
        level = self.keyword_chains
        for i in range(len(chars)):
            if chars[i] in level:
                level = level[chars[i]]
            else:
                if not isinstance(level, dict):
                    break
                for j in range(i, len(chars)):
                    level[chars[j]] = {}
                    last_level, last_char = level, chars[j]
                    level = level[chars[j]]
                last_level[last_char] = {self.delimit: 0}
                break
        if i == len(chars) - 1:
            level[self.delimit] = 0

    # def parse(self, path):
    #     with open(path,encoding='utf-8') as f:
    #         for keyword in f:
    #             # print(keyword)
    #             self.add(str(keyword).strip())

    # 加载敏感词函数
    def parse(self, data):
        for i in data['lable']:
            self.add(str(i).strip())

    def filter(self, message, repl="*"):
        message = message.lower()
        ret = []
        start = 0
        hit_word=[]
        while start < len(message):
            level = self.keyword_chains
            step_ins = 0
            for char in message[start:]:
                if char in level:
                    step_ins += 1
                    if self.delimit not in level[char]:
                        level = level[char]
                    else:
                        # print(step_ins)
                        ret.append(repl * step_ins)
                        # print("%s--------step_ins" %step_ins)
                        start += step_ins - 1
                        # print("%s--------start" %start)
                        kk=message[start-step_ins+1:start+1]
                        hit_word.append(kk)
                        break
                else:
                    ret.append(message[start])
                    # print(message[start])
                    break
            else:
                ret.append(message[start])
            start += 1

        return hit_word

英文DFA算法过滤敏感词改进版本

# 英文DFA算法
class English_DFAFilter():
    def __init__(self):
        self.keyword_chains = {}
        self.delimit = '\x00'

    def find_english_word_last_index(self,message):
        """

        :param sentence: 英文句子
        :return: 返回英文句子的每个单词最后的字母的索引
        """
        last_index_list = []
        for i, j in enumerate(message):
            # print(i, j)
            if j == ' ':
                last_index_list.append(i - 1)
        last_index_list.append(len(message) - 1)
        print(last_index_list)
        return last_index_list

    def add(self, keyword):
        keyword = keyword.lower()
        chars = keyword.strip()
        if not chars:
            return
        level = self.keyword_chains
        for i in range(len(chars)):
            if chars[i] in level:
                level = level[chars[i]]
            else:
                if not isinstance(level, dict):
                    break
                for j in range(i, len(chars)):
                    level[chars[j]] = {}
                    last_level, last_char = level, chars[j]
                    level = level[chars[j]]
                last_level[last_char] = {self.delimit: 0}
                break
        if i == len(chars) - 1:
            level[self.delimit] = 0

    # def parse2(self, path):
    #     with open(path,encoding='utf-8') as f:
    #         for keyword in f:
    #             # print(keyword)
    #             self.add(str(keyword).strip())

    # 加载敏感词函数
    def parse(self, data):
        for i in data['lable']:
            self.add(str(i).strip())

    def filter(self, message, repl="*"):
        message = message.lower()
        ret = []
        start = 0
        hit_word=[]
        while start < len(message):
            level = self.keyword_chains

            step_ins = 0
            for char in message[start:]:
                if char in level:
                    step_ins += 1
                    if self.delimit not in level[char]:
                        level = level[char]
                    else:
                        # print(step_ins)
                        ret.append(repl * step_ins)
                        # print("%s--------step_ins" %step_ins)
                        start += step_ins - 1
                        # print("%s--------start" %start)

                        # 判断找到是否是每个单词的最后一个字母的索引

                        if start  in self.find_english_word_last_index(message):
                            kk=message[start-step_ins+1:start+1]
                            hit_word.append(kk)

                        break
                else:
                    ret.append(message[start])
                    # print(message[start])
                    break
            else:
                ret.append(message[start])
            start += 1

        return hit_word