Python 使用布尔检索提取文件+；最大似然算法

我试图创建一个程序，从一个目录中提取文件，而不知道基于文档中写入的文本的文件名。使用布尔检索+ML算法（稍后我将添加该算法，因为现在正在处理布尔检索），在输入查询时，我接收到错误，但文档中存在单词。请帮我渡过难关

Enter your query: profit
[]
profit  not found
[]
[]
---------------------------------------------------------------------------
IndexError                                Traceback (most recent call last)
<ipython-input-100-d08da3ab4dc8> in <module>()
     55 files = []
     56 print(zeroes_and_ones_of_all_words)
---> 57 lis = zeroes_and_ones_of_all_words[0]
     58 cnt = 1
     59 for index in lis:

IndexError: list index out of range

除此之外，如果有任何想法建议如何使用ML和AI方法通过关键字提取文件，那将是非常棒的。

---

谢谢

请阅读标签的说明。

import nltk 
nltk.download("stopwords")
nltk.download("punkt")
from nltk.corpus import stopwords 
from nltk.stem import WordNetLemmatizer, PorterStemmer 
from nltk.tokenize import sent_tokenize , word_tokenize
import glob 
import re 
import os 
import numpy as np 
import sys 
Stopwords = set(stopwords.words('english'))

all_words = []
dict_global = {}
file_folder = 'data/*'

idx =1
files_with_index = {}
for file in glob.glob(file_folder):
  print(file)
  fname = file
  file = open(file,"r")
  text = file.read()
  text = remove_special_characters(text)
  text = re.sub(re.compile('\d'),'',text)
  sentences = sent_tokenize(text)
  words = word_tokenize(text)
  words = [word for word in words if len(words)>1]
  words = [word.lower() for word in words]
  words = [word for word in words if word not in Stopwords]
  dict_global.update(finding_all_unique_words_and_freq(words))
  files_with_index[idx] = os.path.basename(fname)
  idx = idx + 1
  
unique_words_all = set(dict_global.keys())

def finding_all_unique_words_and_freq(words):
    words_unique = []
    word_freq = {}
    for word in words:
        if word not in words_unique:
            words_unique.append(word)`enter code here`
    for word in words_unique:
        word_freq[word] = words.count(word)
    return word_freq
def finding_freq_of_word_in_doc(word,words):
    freq = words.count(word)
        
def remove_special_characters(text):
    regex = re.compile('[^a-zA-Z0-9\s]')
    text_returned = re.sub(regex,'',text)
    return text_returned
class Node:
    def __init__(self ,docId, freq = None):
        self.freq = freq
        self.doc = docId
        self.nextval = None
    
class SlinkedList:
    def __init__(self ,head = None):
        self.head = head

linked_list_data = {}
for word in unique_words_all:
    linked_list_data[word] = SlinkedList()
    linked_list_data[word].head = Node(1,Node)
word_freq_in_doc = {}
idx = 1
for file in glob.glob(file_folder):
    file = open(file, "r")
    text = file.read()
    text = remove_special_characters(text)
    text = re.sub(re.compile('\d'),'',text)
    sentences = sent_tokenize(text)
    words = word_tokenize(text)
    words = [word for word in words if len(words)>1]
    words = [word.lower() for word in words]
    words = [word for word in words if word not in Stopwords]
    word_freq_in_doc = finding_all_unique_words_and_freq(words)
    for word in word_freq_in_doc.keys():
        linked_list = linked_list_data[word].head
        while linked_list.nextval is not None:
            linked_list = linked_list.nextval
        linked_list.nextval = Node(idx ,word_freq_in_doc[word])
    idx = idx + 1

query = input('Enter your query:')
query = word_tokenize(query)
connecting_words = []
cnt = 1
different_words = []
for word in query:
    if word.lower() != "and" and word.lower() != "or" and word.lower() != "not":
        different_words.append(word.lower())
    else:
        connecting_words.append(word.lower())
print(connecting_words)



total_files = len(files_with_index)
zeroes_and_ones = []
zeroes_and_ones_of_all_words = []

for word in (different_words):
    if word.lower() in unique_words_all:
        zeroes_and_ones = [0] * total_files
        linkedlist = linked_list_data[word].head
        print(word)
        while linkedlist.nextval is not None:
            zeroes_and_ones[linkedlist.nextval.doc - 1] = 1
            linkedlist = linkedlist.nextval
        zeroes_and_ones_of_all_words.append(zeroes_and_ones)
    else:
        print(word," not found")
        
print(zeroes_and_ones_of_all_words)

for word in connecting_words:
    word_list1 = zeroes_and_ones_of_all_words[0]
    word_list2 = zeroes_and_ones_of_all_words[1]
    if word == "and":
        bitwise_op = [w1 & w2 for (w1,w2) in zip(word_list1,word_list2)]
        zeroes_and_ones_of_all_words.remove(word_list1)
        zeroes_and_ones_of_all_words.remove(word_list2)
        zeroes_and_ones_of_all_words.insert(0, bitwise_op);
    elif word == "or":
        bitwise_op = [w1 | w2 for (w1,w2) in zip(word_list1,word_list2)]
        zeroes_and_ones_of_all_words.remove(word_list1)
        zeroes_and_ones_of_all_words.remove(word_list2)
        zeroes_and_ones_of_all_words.insert(0, bitwise_op);
    elif word == "not":
        bitwise_op = [not w1 for w1 in word_list2]
        bitwise_op = [int(b == True) for b in bitwise_op]
        zeroes_and_ones_of_all_words.remove(word_list2)
        zeroes_and_ones_of_all_words.remove(word_list1)
        bitwise_op = [w1 & w2 for (w1,w2) in zip(word_list1,bitwise_op)]
        zeroes_and_ones_of_all_words.insert(0, bitwise_op);
        
 
files = []    
print(zeroes_and_ones_of_all_words)
lis = zeroes_and_ones_of_all_words[0]
cnt = 1
for index in lis:
    if index == 1:
        files.append(files_with_index[cnt])
    cnt = cnt+1
    
print(files)