Natural language understandingNamed entity recognitionThis article provides an overview of modern natural language processing and understanding methods. All the monitored technologies are covered in the context of search engines. The authors do not......
This Special Issue highlights the most recent research being carried out in the NLP field to discuss relative open issues, with a particular focus on both emerging approaches for language learning, understanding, production, and grounding interactively or autonomously from data in cognitive and neur...
Different software environments are useful throughout the said processes. For example, the Natural Language Toolkit (NLTK) is a suite of libraries and programs for English that is written in the Python programming language. It supports text classification, tokenization, stemming, tagging, parsing and ...
Natural language processing includes many different techniques for interpreting human language, ranging from statistical and machine learning methods to rules-based and algorithmic approaches. We need a broad array of approaches because the text- and voice-based data varies widely, as do the practical ...
Natural language processing (NLP) is a branch of artificial intelligence (AI) that analyzes the interaction of humans and computers via natural language. It requires developing algorithms and computational models to process and reproduce human speech. The growth of digital data and the necessity for ...
discussions which were likely needed prior to moving ahead. The first of those topics is will be covered here, more of a general discussion on the approaches to natural language processing tasks which are common today. This also brings up the question: specifically, what types of NLP tasks ...
回译+对抗训练,通过有机地集成多个转换来合成多样化和信息丰富的增强数据。 回译+鉴别器过滤反向翻译结果中的句子,提升了增强数据的质量。 做法二:单向翻译,常用在多语场景。 模型生成 做法一:将去词法化的输入话语和指定的不同秩 k 作为输入提供给 Seq2Seq 模型以生成新的话语。
Language Models:给定label,利用语言模型生成样本,他们用GPT-2生成有标签的句子,并提前在训练集上进行微调。然后通过分类器对数据增强的句子进行过滤,以保证数据质量。Kumar等人。有点像前阵子看的谷歌UDG。有些研究会加个判别模型过滤。 Self-training:先有监督训练一个模型,再给无监督数据打一些标签。 作者依旧贴心...
Current approaches to natural language processing are based on deep learning, a type of AI that examines and uses patterns in data to improve a program's understanding. Deep learning models require massive amounts of labeled data for the natural language processing algorithm to train on and identi...
Natural language processing (NLP) is a subfield of artificial intelligence (AI) that uses machine learning to help computers communicate with human language.