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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.
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 ...
Mathematica – provides built in tools for text alignment, pattern matching, clustering and semantic analysis. See Wolfram Language, the programming language of Mathematica. MATLAB offers Text Analytics Toolbox for importing text data, converting it to numeric form for use in machine and deep learning, sentiment analysis and classification ...
LangChain is a software framework that helps facilitate the integration of large language models (LLMs) into applications. 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.
The term is roughly synonymous with text mining; indeed, Ronen Feldman modified a 2000 description of "text mining" [6] in 2004 to describe "text analytics". [7] The latter term is now used more frequently in business settings while "text mining" is used in some of the earliest application areas, dating to the 1980s, [ 8 ] notably life-sciences ...
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 ...
An ideal multi-document summarization system not only shortens the source texts, but also presents information organized around the key aspects to represent diverse views. Success produces an overview of a given topic. Such text compilations should also follow basic requirements for an overview text compiled by a human.
Auto-text is a portion of a text preexisting in the computer memory, available as a supplement to newly composed documents, and suggested to the document author by software. A block of auto-text can contain a few letters , words , sentences or paragraphs . [ 1 ]