Text summarization techniques are methods used to condense large volumes of text into shorter, more digestible summaries while retaining the essential information. There are two main types: extractive summarization, which selects key sentences or phrases directly from the original text, and abstractive summarization, which generates new sentences that capture the main ideas in a more concise form. These techniques are widely used in various applications, such as news aggregation, academic research, and content curation. By employing algorithms and natural language processing, these methods help users quickly grasp the core message of lengthy documents, saving time and enhancing information accessibility.