Natural language processing (NLP) is a field of computer science that studies how computers and humans interact. In the 1950s, Alan Turing published an article that proposed a measure of intelligence, now called the Turing test. More modern techniques, such as deep learning, have produced ...
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Natural Language Processing in Clojure with clojure-opennlp Context searching using Clojure-OpenNLP Read the source from Marginalia http://dakrone.github.com/clojure-opennlp/ Known Issues When using the treebank-chunker on a sentence, please ensure you have a period at the end of the sentence,...
Keywords: Language model, pre-training, natural language understanding, natural language generation URLs: Paper , GitHub 论文简要 : 本文提出了一种新的统一的预训练语言模型(UNILM),可以用于自然语言理解和生成任务。通过使用三种类型的语言建模任务进行预训练,该模型在多个任务上取得了优秀的性能,并在五个自然语...
【预训练语言模型】MacBERT: Revisiting Pre-trained Models for Chinese Natural Language Processing 简要信息: 一、动机 在一些较为复杂的QA任务上,BERT等一系列的预训练语言模型可以达到很高的效果; 训练transformer-based预训练模型比较困难; 大多数的语言模型是基于英语的,很少有工作致力于提升中文语言模型的提升; ...
目录 致谢 入门须知 Chapter1.基础介绍 Chapter2.传统NLP快速回顾 Chapter3.神经网络基础组件 Chapter4.自然语言处理Feed-ForwardNetworks Chapter5.EmbeddingWordsandTypes Chapter6.自然语言处理SequenceModeling Chapter7.自然语言处理的中间SequenceModeling Chapter8.用于自然语言处理的高级Sequence Chapter9.经典,前沿和后续...
Recurrent Neural Networks and Natural Language Processing 先道个歉:拖着这么久才更新。第五章的后续几章已经翻译出来了,占时没有时间调试程序。所以也没有更新。等调试完程序以后,我会放到这里来。 书籍封面 此处给出本节的代码:https://github.com/Leechen2014/TensorFlow-for-Machine-Intelligence ...
'answer': 'Natural language processing'} What was once the fantasy of a distant future is not only here but is accessible to anyone with a computer and an internet connection. The ability to understand and communicate in natural language, one of the most valuable assets that humanity has deve...
NLP中的范式转移和统一范式:Paradigm Shift in Natural Language Processing 1、Introduction 2、Paradigms in NLP 3、Paradigm Shift in NLP Tasks 4、Potential Unified Paradigms in NLP 5、结论 参考文献 原论文地址: arxiv.org/abs/2109.1257 github: github.com/txsun1997/nl 1、Introduction 范式(paradigm)就...
1.2 context feature token feature from n tokens before and n tokens after word n-grams, n=2,3,4 skip-n-grams 1.3 sentence features sentence length case-folding patterns presence of digits enumeration tokens at the start a colon at the end ...