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Image collection summarization is another application example of automatic summarization. It consists in selecting a representative set of images from a larger set of images. [13] A summary in this context is useful to show the most representative images of results in an image collection exploration system. Video summarization is a related ...
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 ...
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.
Right now, his team is building an “automatic summarization” feature, which will be a one-line summary thread near the subject of the email that will briefly summarize its contents. In the ...
Google is making it easy to catch up on long documents with a new auto summarization feature, which will soon be available on Google Docs. Google is bringing automatic summaries to Docs and Chat ...
Recently, submodular functions have also found utility in several real world problems in machine learning and artificial intelligence, including automatic summarization, multi-document summarization, feature selection, active learning, sensor placement, image collection summarization and many other domains. [1] [2] [3] [4]
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 ...
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.
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