请帮我写出上述问题代码
时间: 2024-03-25 11:38:13 浏览: 23
这个任务涉及的内容比较多,需要较长的代码实现过程,以下是一个简单的示例代码,供参考:
```python
import os
import re
import json
import string
import nltk
import jieba
from nltk.corpus import stopwords
from nltk.stem import WordNetLemmatizer
# 下载停用词和词性还原器
nltk.download('stopwords')
nltk.download('wordnet')
# 初始化停用词和词形还原器
stop_words = set(stopwords.words('english'))
wordnet_lemmatizer = WordNetLemmatizer()
# 初始化同义词词典
synonym_dict = {}
# 初始化倒排记录表
inverted_index = {}
# 初始化文档列表
docs = []
# 初始化位置信息字典
pos_dict = {}
# 读取文档集
def read_docs():
global docs
doc_dir = "doc_dir"
for filename in os.listdir(doc_dir):
with open(os.path.join(doc_dir, filename), 'r') as f:
doc = f.read()
docs.append(doc)
# 分词并去掉停用词和标点符号
def tokenize(doc):
global stop_words
global wordnet_lemmatizer
# 英文文档分词
tokens = nltk.word_tokenize(doc.lower())
# 去掉停用词和标点符号
tokens = [wordnet_lemmatizer.lemmatize(token) for token in tokens if token not in stop_words and token not in string.punctuation]
return tokens
# 分词并去掉停用词和标点符号
def tokenize_chinese(doc):
global stop_words
# 中文文档分词
tokens = jieba.lcut(doc)
# 去掉停用词和标点符号
tokens = [token for token in tokens if token not in stop_words and token not in string.punctuation]
return tokens
# 生成同义词词典
def generate_synonym_dict():
global synonym_dict
# 读取同义词词典
with open('synonym_dict.json', 'r') as f:
synonym_dict = json.load(f)
# 生成倒排记录表和位置信息字典
def generate_inverted_index():
global docs
global inverted_index
global pos_dict
for i, doc in enumerate(docs):
tokens = tokenize(doc)
# 生成位置信息字典
pos_dict[i] = {}
for j, token in enumerate(tokens):
if token not in inverted_index:
inverted_index[token] = {}
if i not in inverted_index[token]:
inverted_index[token][i] = []
inverted_index[token][i].append(j)
if j not in pos_dict[i]:
pos_dict[i][j] = []
pos_dict[i][j].append(token)
# 满足布尔条件的检索
def boolean_search(query):
global inverted_index
# 构造布尔查询表达式
query = query.strip().split()
if len(query) == 0:
return []
if len(query) == 1:
if query[0] not in inverted_index:
return []
else:
return [doc_id for doc_id in inverted_index[query[0]].keys()]
stack = []
operators = set(['AND', 'OR', 'NOT'])
for token in query:
if token.upper() in operators:
operator = token.upper()
right = stack.pop()
left = stack.pop() if len(stack) > 0 else None
if operator == 'OR':
stack.append(set(left).union(set(right)))
elif operator == 'AND':
stack.append(set(left).intersection(set(right)))
elif operator == 'NOT':
stack.append(set(left).difference(set(right)))
else:
if token not in inverted_index:
stack.append(set())
else:
stack.append(set(inverted_index[token].keys()))
if len(stack) == 0:
return []
else:
return list(stack.pop())
# 短语查询
def phrase_search(query):
global inverted_index
global pos_dict
# 构造短语查询表达式
query = query.strip().split()
if len(query) == 0:
return []
if len(query) == 1:
if query[0] not in inverted_index:
return []
else:
return [doc_id for doc_id in inverted_index[query[0]].keys()]
phrase_positions = []
for i, token in enumerate(query):
if token in inverted_index:
for doc_id, positions in inverted_index[token].items():
if i == 0:
phrase_positions.extend([(doc_id, pos) for pos in positions])
else:
for doc_id2, positions2 in phrase_positions:
if doc_id == doc_id2 and (positions2[-1] + 1) in positions:
positions2.append(positions2[-1] + 1)
else:
phrase_positions.remove((doc_id2, positions2))
if len(phrase_positions) == 0:
return []
else:
return list(set([doc_id for doc_id, positions in phrase_positions if len(positions) == len(query)]))
# 查询扩展
def query_expansion(query):
global synonym_dict
global inverted_index
# 同义词扩展
expanded_query = set(query.strip().split())
for token in query.strip().split():
if token in synonym_dict:
expanded_query = expanded_query.union(set(synonym_dict[token]))
# 音似词扩展
for token in query.strip().split():
soundex = nltk.soundex(token)
for token2 in inverted_index.keys():
if soundex == nltk.soundex(token2) and token2 not in expanded_query:
expanded_query.add(token2)
return ' '.join(expanded_query)
# 主函数
if __name__ == '__main__':
read_docs()
generate_synonym_dict()
generate_inverted_index()
query = "information retrieval"
print("原始查询:", query)
print("布尔检索结果:", boolean_search(query))
print("短语查询结果:", phrase_search(query))
expanded_query = query_expansion(query)
print("扩展查询:", expanded_query)
print("扩展查询结果:", boolean_search(expanded_query))
```
以上代码可以实现基本的搜索功能,但还有很多可以优化的地方,例如对中文文档的处理、使用更高效的数据结构存储倒排记录表、使用更复杂的查询扩展方法等。
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