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Natural language processing [PDF]
Annual Review of Information Science and Technology, 2003 Beginning with the basic issues of NLP, this chapter aims to chart the major research activities in this area since the last ARIST Chapter in 1996 (Haas, 1996), including: (i) natural language text processing systems - text summarization, information ...
Adams +101 more
core +5 more sources
Robust Processing of Natural Language [PDF]
, 1995 Previous approaches to robustness in natural language processing usually treat deviant input by relaxing grammatical constraints whenever a successful analysis cannot be provided by ``normal'' means. This schema implies, that error detection always comes
Menzel, Wolfgang
core +6 more sources
Revisiting Pre-Trained Models for Chinese Natural Language Processing [PDF]
Findings, 2020 Bidirectional Encoder Representations from Transformers (BERT) has shown marvelous improvements across various NLP tasks, and consecutive variants have been proposed to further improve the performance of the pre-trained language models. In this paper, we
Che, Wanxiang +5 more
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Natural Language Processing [PDF]
IEEE Expert, 1994 The subject of Natural Language Processing can be considered in both broad and narrow senses. In the broad sense, it covers processing issues at all levels of natural language understanding, including speech recognition, syntactic and semantic analysis ...
Steedman, Mark
core +6 more sources
A Primer on Neural Network Models for Natural Language Processing [PDF]
arXiv, 2015 Over the past few years, neural networks have re-emerged as powerful machine-learning models, yielding state-of-the-art results in fields such as image recognition and speech processing. More recently, neural network models started to be applied also to textual natural language signals, again with very promising results.
Yoav Goldberg
arxiv +3 more sources
Natural Language Processing. [PDF]
, 2001 Natural Language Processing (NLP) is the computerized approach to analyzing text that is based on both a set of theories and a set of technologies. And, being a very active area of research and development, there is not a single agreed-upon definition ...
Liddy, Elizabeth D.
openalex +4 more sources
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing [PDF]
ACM Computing Surveys, 2021 This article surveys and organizes research works in a new paradigm in natural language processing, which we dub “prompt-based learning.” Unlike traditional supervised learning, which trains a model to take in an input x and predict an output y as P(y|x),
Pengfei Liu +5 more
semanticscholar +1 more source
Natural Language Processing [PDF]
International Journal of Advances in Scientific Research and Engineering, 2018 Natural language processing (NLP) refers to the field of study that focuses on the interactions between human language and computers. It is a computational approach to text analysis. It is the application of a wide range of computational techniques for the understanding, automatic analysis, and representation of human language.
Yu Zhou +2 more
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Attention in Natural Language Processing [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2021 Attention is an increasingly popular mechanism used in a wide range of neural architectures. The mechanism itself has been realized in a variety of formats. However, because of the fast-paced advances in this domain, a systematic overview of attention is still missing.
Andrea Galassi +2 more
openaire +4 more sources
Organizing an in-class hackathon to correct PDF-to-text conversion errors of 1.0 [PDF]
Genomics & Informatics, 2020 This paper describes a community effort to improve earlier versions of the full-text corpus of Genomics & Informatics by semi-automatically detecting and correcting PDF-to-text conversion errors and optical character recognition errors during the first ...
Sunho Kim +44 more
doaj +1 more source