Unsupervised Extractive Summarization

Unsupervised extractive summarization is a technique in the field of natural language processing aimed at automatically extracting key sentences or segments from large amounts of text data to generate concise and clear summaries. This method does not require labeled data; instead, it identifies important information within the text through algorithms, achieving efficient information condensation. Its primary goal is to enhance the efficiency of information retrieval, reduce reading time, and help users quickly obtain core content. It has broad application value in areas such as news summarization, literature reviews, and intelligence analysis.