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Current Approaches and Applications in Natural Language Processing

Current approaches to Natural Language Processing (NLP) have shown impressive improvements in many important tasks: machine translation, language modeling, text generation, sentiment/emotion analysis, natural language understanding, and question answering, among others. The advent of new methods and...

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Bibliographic Details
Main Author:	Montejo-Ráez, Arturo
Other Authors:	Jiménez-Zafra, Salud María
Format:	eBook
Language:	English
Published:	Basel 2022
Subjects:	Machine Learning Multi-modal Language Model Relevance Feedback Feature Fusion Multilingual Pre-trained Language Model Distributional Semantics Robbert Quality Estimation Named-entity Recognition Transformer Models Deep Learning Predictive Model Transitive Closure Arabic Task-oriented Dialogue Systems Neural Networks Machine Learning Classifiers History Of Engineering & Technology / Bicssc Conditional Random Field Word Embeddings Liwc Wmt Multi-lingual Transformer Model Multinomial Naive Bayes Technology: General Issues / Bicssc Slot Filling Query Expansion Dual Multi-head Attention Relationship Extraction Attention Mechanism Conceptual Modeling Abstractive Summarization Linguistic Corpus Automatic Classification Latin American Spanish Language Models Conversational Ai Geospatial Data Technology And Application Multisource Feature Extraction Linguistic Cues Multi-modal Dataset Machine Reading Comprehension Natural Language Processing Data Privacy Entity Linking Trend Analysis Word Co-occurrence Unbalanced Data Problem Fine-grained Named Entity Recognition Machine Translation Spacy Problem-solution Pattern Language Model Wikimedia Commons Intent Detection Fasttext Text Classification Semantic Analysis Discriminant Function Analysis K-stacked Feature Fusion Lime Language Marker N/a Electronic Health Records Fake News Detection Bert Model Retrieval-based Question Answering Document Representation Knowledge Graph Deep Neural Networks Personality Recognition Social Media Neural Machine Translation Information Retrieval Disc Model Pre-trained Model Cause-effect Relation Dual-stacked Output Universal Representation Multilingual Models Transfer Learning Mental Disorder Stance Detection Text Analysis Sentiment Analysis Question Answering Entity Embedding Curriculum Learning Concreteness Recurrent Neural Networks Topic Modeling Inter-information Relationship Transformer Deception Bert Question Difficult Estimation Statistical Analysis Mt5 Clinical Text Global Model Attention Model Fine-tuning Automatic Hate Speech Detection Named Entity Recognition Monolingual Models Federated Learning Query Generation Discourse Analysis Pretrained Language Model
Online Access:	https://directory.doabooks.org/handle/20.500.12854... https://www.mdpi.com/books/pdfview/book/5892
Collection:	Directory of Open Access Books - Collection details see MPG.ReNa

Description
Summary:	Current approaches to Natural Language Processing (NLP) have shown impressive improvements in many important tasks: machine translation, language modeling, text generation, sentiment/emotion analysis, natural language understanding, and question answering, among others. The advent of new methods and techniques, such as graph-based approaches, reinforcement learning, or deep learning, have boosted many NLP tasks to a human-level performance (and even beyond). This has attracted the interest of many companies, so new products and solutions can benefit from advances in this relevant area within the artificial intelligence domain.This Special Issue reprint, focusing on emerging techniques and trendy applications of NLP methods, reports on some of these achievements, establishing a useful reference for industry and researchers on cutting-edge human language technologies.
Item Description:	Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:	1 electronic resource (476 p.)
ISBN:	9783036544397 books978-3-0365-4440-3 9783036544403

Current Approaches and Applications in Natural Language Processing

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