输出

输出.py

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+import re
+import pandas as pd
+from collections import Counter
+
+# 读取文本
+def read_file(file_path):
+    with open(file_path, 'r', encoding='utf-8') as file:
+        return file.read()
+
+
+# 将文本拆分为句子
+def split_into_sentences(text):
+    # 使用正则表达式将文本分割
+    sentences = re.split(r'[.!?。！？]', text)
+    return [sentence.strip() for sentence in sentences if sentence.strip()]
+
+# 查找包含关键词的句子并统计关键词出现次数
+def find_top_sentences_by_keyword(sentences, keyword, top_n=8):
+    keyword_counts = []
+    for sentence in sentences:
+        count = sentence.lower().count(keyword.lower())
+        if count > 0:
+            keyword_counts.append((sentence, count))
+
+    # 根据关键词出现次数排序，并取前n个
+    keyword_counts.sort(key=lambda x: x[1], reverse=True)
+    return [sentence for sentence, _ in keyword_counts[:top_n]]
+
+
+# 将结果保存到TXT文件中
+def save_to_file(file_path, keyword, sentences):
+    with open(file_path, 'a', encoding='utf-8') as file:
+        file.write(f"关键词: {keyword}\n")
+        for i, sentence in enumerate(sentences, 1):
+            file.write(f"{i}. {sentence}\n")
+        file.write("\n")  # 分隔不同关键词的结果
+
+
+# 主函数
+def main():
+    # 输入TXT文件路径
+    input_file = '3.txt'
+    output_file = 'output.txt'
+    # 要查找的关键词列表
+    keywords = [
+    'AI', '人工智能', '机器学习', '深度学习', '神经网络', '自动化', '算法', '数据科学',
+    '自然语言处理', '计算机视觉',  '人工智能技术', 'AI技术', 'AI应用', 'AI模型',
+    '大数据', '预测分析', '机器视觉', '自动驾驶',
+     '智能推荐', '计算机科学', '人工智能应用',
+    '数据分析','智能化', '情感计算','ai','字幕','推荐','gpt','机器','直播','机翻','实时','技术'
+]
+
+    # 读取文本并拆分为句子
+    text = read_file(input_file)
+    sentences = split_into_sentences(text)
+
+    # 对每个关键词查找出现次数前八的句子
+    for keyword in keywords:
+        top_sentences = find_top_sentences_by_keyword(sentences, keyword, top_n=8)
+        save_to_file(output_file, keyword, top_sentences)
+if __name__ == "__main__":
+    main()
+
+