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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.
Thankfully, researchers at the Allen Institute for Artificial Intelligence have developed a new model to summarize text from scientific papers, and present it in a few sentences in the form of TL ...
An example of a summarization problem is document summarization, which attempts to automatically produce an abstract from a given document. Sometimes one might be interested in generating a summary from a single source document, while others can use multiple source documents (for example, a cluster of articles on the same topic).
The file starts with a header containing a magic number (as a readable string) and the version of the format, for example %PDF-1.7. The format is a subset of a COS ("Carousel" Object Structure) format. [23] A COS tree file consists primarily of objects, of which there are nine types: [16] Boolean values, representing true or false; Real numbers ...
The Portable Document Format (PDF) is a file format used to present documents in a manner independent of application software, hardware, and operating systems. Each PDF file encapsulates a complete description of the presentation of the document, including the text, fonts, graphics, and other information needed to display it.
The informative abstract, also known as the complete abstract, is a compendious summary of a paper's substance and its background, purpose, methodology, results, and conclusion. [23] [24] Usually between 100 and 200 words, the informative abstract summarizes the paper's structure, its major topics and key points. [23]
Related: The 26 Funniest NYT Connections Game Memes You'll Appreciate if You Do This Daily Word Puzzle. Hints About Today's NYT Connections Categories on Friday, December 13. 1. These are commonly ...
ROUGE, or Recall-Oriented Understudy for Gisting Evaluation, [1] is a set of metrics and a software package used for evaluating automatic summarization and machine translation software in natural language processing. The metrics compare an automatically produced summary or translation against a reference or a set of references (human-produced ...
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