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2. Automatic summarization - Wikipedia

   en.wikipedia.org/wiki/Automatic_summarization

   Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.

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4. YandexGPT - Wikipedia

   en.wikipedia.org/wiki/YandexGPT

   YandexGPT is a neural network of the GPT family developed by the Russian company Yandex LLC.YandexGPT can create and revise texts, generate new ideas and capture the context of the conversation with the user.

5. Wikipedia:How to write a plot summary - Wikipedia

   en.wikipedia.org/wiki/Wikipedia:How_to_write_a...

   A plot summary is not a recap. It should not cover every scene or every moment of a story. A summary is not meant to reproduce the experience of reading or watching the work. In fact, readers might be here because they didn't understand the original. Just repeating what they have already seen or read is unlikely to help them.

6. Wikipedia:Source your plot summaries - Wikipedia

   en.wikipedia.org/wiki/Wikipedia:Source_your_plot...

   Wikipedia articles concerning fiction frequently feature overly long or excessively detailed plot summaries. While any plot section can be trimmed, it can be hard to know what to cut if one hasn't consumed the relevant media, while those who have might be tempted to explain any intricacy that arises to give the reader the full experience of the show.

7. Storyland (narrative generator) - Wikipedia

   en.wikipedia.org/.../Storyland_(narrative_generator)

   Storyland is a browser-based narrative work of electronic literature.The project is included in the first Electronic Literature Collection. [1] It was created by Nanette Wylde in 2000 and is considered a form of Combinatory Narrative or Generative Poetry which is created with the use of the computer's random function.

8. Multi-document summarization - Wikipedia

   en.wikipedia.org/wiki/Multi-document_summarization

   Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. The resulting summary report allows individual users, such as professional information consumers, to quickly familiarize themselves with information contained in a large cluster of documents.

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