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Automatic summarization is the process of shortening a set of data computationally, to create a subset (a summary) that represents the most important or relevant information within the original content. Artificial intelligence algorithms are commonly developed and employed to achieve this, specialized for different types of data.
Resoomer provides an online tool that can summarize any text regardless of the length and nature of the document (press article, scientific journal, essay, book, etc.). [6] [7] Google Chrome and Mozilla Firefox browser extensions are also available. [8] The platform has also set up a reading assistant that offers full reading of the summary out ...
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. In such a way ...
Wordtune. Wordtune is an AI powered reading and writing companion capable of fixing grammatical errors, understanding context and meaning, suggesting paraphrases or alternative writing tones, and generating written text based on context. [ 1][ 2][ 3] It is developed by the Israeli AI company AI21 Labs. [ 4][ 5][ 6][ 7]
Text-to-Text Transfer Transformer (T5) T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI. Introduced in 2019, [ 1][ 2] T5 models are trained on a massive dataset of text and code using a text-to-text framework. The T5 models are capable of performing the text-based tasks that they were pretrained ...
LangChain.com. LangChain is a framework designed to simplify the creation of applications using large language models (LLMs). As a language model integration framework, LangChain's use-cases largely overlap with those of language models in general, including document analysis and summarization, chatbots, and code analysis.
Apache 2.0. Website. arxiv .org /abs /1810 .04805. Bidirectional Encoder Representations from Transformers ( BERT) is a language model introduced in October 2018 by researchers at Google. [ 1][ 2] It learned by self-supervised learning to represent text as a sequence of vectors. It had the transformer encoder architecture.
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 ...
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