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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.
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.
There's almost always a way to rephrase imprecise words instead of using modifiers: "The boy sees a dead body." → "The boy sees a corpse." "Body" is a word of Germanic origin that can refer to living or dead people; "corpse" is a word of Latin origin that can only refer to a dead person. Streamline modifiers that don't add useful detail:
MDI: Overlappable windows: each opened document gets its own fully movable window inside the editor environment. MDI: Tabbed document interface: multiple documents can be viewed as tabs in a single window. MDI: Window splitting: splitting application window to show multiple documents (non-overlapping windows).
For avoidance of plagiarism of text copied from compatibly licensed copyleft publications and public domain publications, see also the section below: Copying material from free sources. You can avoid plagiarism by summarizing source material in your own words followed by an inline citation, or by quoting or closely paraphrasing the source ...
You might think you know what plagiarism is, and how to avoid it. But Wikipedia is a little bit different. The rules cover not only copy-and-paste plagiarism, but also close paraphrasing and copyright violations. And the stakes are high: the consequences of committing plagiarism in a Wikipedia class assignment are the same as handing in a paper ...
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The free model uses the company's standalone LLM based on GPT-3.5 with browsing. [ 6 ] [ 7 ] It uses the context of the user queries to provide a personalized search result. Perplexity summarizes the search results and produces text with inline citations. [ 7 ]
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related to: how to summarize without plagiarizing words for free windows 10 for pc 64 bit