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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.

  3. Sentence extraction - Wikipedia

    en.wikipedia.org/wiki/Sentence_extraction

    Sentence extraction is a technique used for automatic summarization of a text. In this shallow approach, statistical heuristics are used to identify the most salient sentences of a text. Sentence extraction is a low-cost approach compared to more knowledge-intensive deeper approaches which require additional knowledge bases such as ontologies ...

  4. Problem statement - Wikipedia

    en.wikipedia.org/wiki/Problem_statement

    The main purpose of a problem statement is to identify and explain the problem. [3] [4] Another function of the problem statement is as a communication device. [3] Before the project begins, stakeholders verify the problem and goals are accurately described in the problem statement. Once approved, the project reviews it.

  5. Seq2seq - Wikipedia

    en.wikipedia.org/wiki/Seq2seq

    Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise). seq2seq is an approach to machine translation (or more generally, sequence transduction) with roots in information theory, where communication is understood as an encode-transmit-decode process, and machine translation can be studied as a ...

  6. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...

  7. Text summarization - Wikipedia

    en.wikipedia.org/?title=Text_summarization&...

    This page was last edited on 13 October 2021, at 13:46 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.

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