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Natural Language Processing is a bimonthly peer-reviewed academic journal published by Cambridge University Press which covers research and software in natural language processing. It was established in 1995 as Natural Language Engineering , obtaining its current title in 2024.
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
Natural Language Processing 2021 [114] Nguyen et al. PG-19: A set of books extracted from the Project Gutenberg books library Text Natural Language Processing 2019 Jack W et al. Deepmind Mathematics: Mathematical question and answer pairs. Text Natural Language Processing 2018 [115] D Saxton et al. Anna's Archive
It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity. The bag-of-words model is commonly used in methods of document classification where, for example, the (frequency of) occurrence of each word is used as a feature for training a ...
Textual entailment measures natural language understanding as it asks for a semantic interpretation of the text, and due to its generality remains an active area of research. Many approaches and refinements of approaches have been considered, such as word embedding , logical models, graphical models, rule systems, contextual focusing, and ...
UBY-LMF [3] [4] is a format for standardizing lexical resources for Natural Language Processing (NLP). [5] UBY-LMF conforms to the ISO standard for lexicons: LMF, designed within the ISO-TC37, and constitutes a so-called serialization of this abstract standard. [6]
In statistics and natural language processing, a topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. . Topic modeling is a frequently used text-mining tool for discovery of hidden semantic structures in a text
It is notable for its dramatic improvement over previous state-of-the-art models, and as an early example of a large language model. As of 2020, BERT is a ubiquitous baseline in natural language processing (NLP) experiments. [3] BERT is trained by masked token prediction and next sentence prediction.