Summarization

Text summarization is an AI technology that significantly reduces the length of the original text while preserving its core meaning. Depending on the method, it is divided into 'extractive summarization,' which extracts sentences from the original text as they are, and 'abstractive summarization,' which understands the context and reconstructs it into new sentences. In the past, extractive methods with high accuracy were preferred, but with the recent advancement of LLMs (Large Language Models), abstractive methods with natural sentence structures have become the mainstream. When choosing a tool, the key evaluation criteria include not only simple summarization but also the ability to process long documents through large context windows, the suppression of 'hallucinations' (fabricating facts not in the original text), and the capability to structure outputs into user-defined formats (bullet points, tables, summary reports, etc.).