stopword_list = [] with open('dict/stopwords.txt', 'r', encoding='utf8') as f: for word in f.readlines(): stopword_list.append(str(word).strip())

这段代码是用来读取停用词表的。首先定义了一个空列表`stopword_list`，然后打开一个名为`stopwords.txt`的文件，使用`readlines()`方法逐行读取文件内容，并将每行内容去除首尾空格后加入`stopword_list`中。这样，`stopword_list`就包含了停用词表中的所有词语。停用词表是指在文本分析中无需考虑的常见词汇，例如“的”、“是”、“在”等。在文本分析中通常会将这些词语从文本中删除，以提高分析效果和准确性。

相关问题

stopword_path = 'stopwords.txt' stopwords = [line.strip() for line in open(stopword_path, 'r', encoding='utf-8').readlines()]

As an AI language model, I don't have access to files. However, I can explain what this code does:

1. It sets the variable `stopword_path` to the string `'stopwords.txt'`.
2. It opens the file at the path specified by `stopword_path` in read mode (`'r'`) with the encoding `'utf-8'`.
3. It reads all the lines from the file using the `readlines()` method.
4. It strips the newline character (`'\n'`) from each line using the `strip()` method.
5. It creates a list of the stripped lines, which represents the stopwords.
6. It assigns the list of stopwords to the variable `stopwords`.

def chinese_word_cut(mytext): jieba.load_userdict(dic_file) jieba.initialize() try: stopword_list = open(stop_file,encoding ='utf-8') except: stopword_list = []

对于你的第一个问题，我可以帮你解答。这段代码是一个用于中文分词的函数。它使用了jieba库来进行分词操作。首先，它加载了一个自定义的词典文件，以便jieba能够识别更多的词汇。然后，它尝试打开一个停用词文件，并将其读取为一个停用词列表。如果无法打开停用词文件，则停用词列表将为空列表。请问还有其他问题吗？