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Document Structuring is a subtask of Natural language generation, which involves deciding the order and grouping (for example into paragraphs) of sentences in a generated text. It is closely related to the Content determination NLG task. ==Example== Assume we have four sentences which we want to include in a generated text # It will rain on Saturday # It will be sunny on Sunday # Max temperature will be 10C on Saturday # Max temperature will be 15C on Sunday There are 24 (4!) orderings of these messages, including * (1234) It will rain on Saturday. It will be sunny on Sunday. Max temperature will be 10C on Saturday. Max temperature will be 15C on Sunday. * (2341) It will be sunny on Sunday. Max temperature will be 10C on Saturday. Max temperature will be 15C on Sunday. It will rain on Saturday. * (4321) Max temperature will be 15C on Sunday. Max temperature will be 10C on Saturday. It will be sunny on Sunday. It will rain on Saturday. Some of these orderings are better than others. For example, of the texts shown above, human readers prefer (1234) over (2314) and (4321). For any ordering, there are also many ways in which sentences can be grouped into paragraphs and higher-level structures such as sections. For example, there are 8 (2 * *3) ways in which the sentences in (1234) can be grouped into paragraphs, including * (12)(34) :It will rain on Saturday. It will be sunny on Sunday. :Max temperature will be 10C on Saturday. Max temperature will be 15C on Sunday. * (1)(23)(4) :It will rain on Saturday. :It will be sunny on Sunday. Max temperature will be 10C on Saturday. :Max temperature will be 15C on Sunday. As with ordering, human readers prefer some groupings over others; for example, (12)(34) is preferred over (1)(23)(4). The document structuring task is to choose an ordering and grouping of sentences which results in a coherent and well-organised text from the reader's perspective. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Document structuring」の詳細全文を読む スポンサード リンク
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