删除自定义停用词形成python中的短语

Val*_*lav 1 python nlp stop-words python-2.7

我试图在进一步处理输入之前从用户输入中删除某些短语和单词,而在尝试这样做时,我遇到了“索引超出范围”错误的问题,并且完全卡住了。我该如何解决这个问题?我将输入短语作为字符串转换为列表以比较每个单词,并将停用词作为预定义列表。
示例输入:
["well","you","know","the","weather","is","awful"]
["you", "know", "what", "i", " mean", "so", "just", "turn", "the", "lights", "on"]

#Gets user input and removes the selected stop words from it and returns a filtered phrase back.    
def stop_word_remover(phrase_list):

    stop_words_lst = ["yo", "so", "well", "um", "a", "the","you know", "i mean"]

    #initalize clean phrase string
    clean_input_phrase= ""

    #copying phrase_list into a new variable for stopword removal.
    Copy_phrase_list = list(phrase_list)

    #Cleanup loop

    for i in range(1,len(phrase_list)):
        has_stop_words = False

        for x in range(len(stop_words_lst)):
            has_stop_words = False

            #if one of the stop words matches the word passed by the first main loop      the  flag is raised.
            if (phrase_list[i-1]+" "+phrase_list[i]) == stop_words_lst[x].strip():
                has_stop_words = True    

            # this if statement adds the word of the phrase only if the flag is not raised thus making sure all the stop words are filtered out         
            if has_stop_words == True:
                Copy_phrase_list.remove(Copy_phrase_list[i-1])
                Copy_phrase_list.remove(Copy_phrase_list[i-1])

    #first for loop takes a individual words of the phrase given and makes a loop until the whole phrase goes through one word at a time
    for i in range(len(Copy_phrase_list)):
        #flag initialized for marking stop words
        has_stop_words = False

        #second loop takes all the stop words and compares them to the first word passed on by the first loop to sheck for a stop word
        for x in range(len(stop_words_lst)):
            #if one of the stop words matches the word passed by the first main loop the  flag is raised.
            if Copy_phrase_list[i] == stop_words_lst[x].strip():
            has_stop_words = True    

        # this if statement adds the word of the phrase only if the flag is not raised thus making sure all the stop words are filtered out        
        if has_stop_words == False:
            clean_input_phrase += str(Copy_phrase_list[i]) +" "


return clean_input_phrase
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小智 5

使用正则表达式替换函数。用空字符串替换每个匹配项。

stop_words_lst = ['yo', 'so', 'well', 'um', 'a', 'the', 'you know', 'i mean']
s = "you know what i mean so just turn the lights on"

import re
for w in stop_words_lst:
    pattern = r'\b'+w+r'\b'
    s = re.sub(pattern, '', s)
    print (s)
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