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import re
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import pandas as pd
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# 读取文本
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def read_file(file_path):
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with open(file_path, 'r', encoding='utf-8') as file:
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return file.read()
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# 将文本拆分为句子
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def split_into_sentences(text):
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# 使用正则表达式将文本分割
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sentences = re.split(r'[.!?。！？]', text)
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return [sentence.strip() for sentence in sentences if sentence.strip()]
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# 查找包含关键词的句子并统计关键词出现次数
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def find_top_sentences_by_keyword(sentences, keyword, top_n=8):
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keyword_counts = []
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for sentence in sentences:
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count = sentence.lower().count(keyword.lower())
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if count > 0:
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keyword_counts.append((sentence, count))
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# 根据关键词出现次数排序，并取前n个
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keyword_counts.sort(key=lambda x: x[1], reverse=True)
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return [sentence for sentence, _ in keyword_counts[:top_n]]
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# 将结果保存到Excel文件中
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def save_to_excel(file_path, result_dict):
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writer = pd.ExcelWriter(file_path, engine='openpyxl')
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for keyword, sentences in result_dict.items():
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df = pd.DataFrame(sentences, columns=[f'{keyword} '])
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df.to_excel(writer, sheet_name=keyword[:30], index=False)
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writer.close()
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def main():
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input_file = '3.txt'
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output_file = 'results.xlsx'
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# 要查找的关键词列表
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keywords = [
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'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',
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'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',
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'大数据', '预测分析', '机器视觉', '自动驾驶',
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'智能推荐', '计算机科学', '人工智能应用',
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'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'
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]
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# 读取文本并拆分为句子
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text = read_file(input_file)
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sentences = split_into_sentences(text)
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result_dict = {}
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# 对每个关键词查找出现次数前八的句子
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for keyword in keywords:
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top_sentences = find_top_sentences_by_keyword(sentences, keyword, top_n=8)
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result_dict[keyword] = top_sentences
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# 将结果保存到Excel文件
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save_to_excel(output_file, result_dict)
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if __name__ == "__main__":
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main()
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import cProfile
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import pstats
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import 输出
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profiler = cProfile.Profile()
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profiler.enable()
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# 执行主函数
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输出.main()
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profiler.disable()
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# 输出性能分析结果到文本文件
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with open("profile_results1.txt", "w") as f:
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ps = pstats.Stats(profiler, stream=f)
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ps.sort_stats('cumulative')
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ps.print_stats()
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