Natural Language Processing: Emerging Neural Approaches and Applications

• Autore: Esposito Massimo
• Pubblicazione: Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
• Descrizione fisica: 1 online resource (544 p.)
• Soggetto topico: Computer science; Information technology industries
• Soggetto non controllato: adversarial attack; adversarial example; antonymy detection; attention mechanism; attention model; BERT; BERT word embedding; bidirectional long short-term memory (bidirectional LSTM); bidirectional LSTM CRF; bidirectional RNN; bilingual translation; BM25; Cantonese; causal encoder; chief complaint; classification; clinical named entity recognition; cloze test; CNN dictionary; commonsense; conditional random field; CoNLL; context-to-entity attention; contextual features; conversation knowledge; convolutional neural networks; convolutional neural networks (CNN); cross-lingual classification; deep learning; deep learning (DL); deep learning NER; deep neural networks; delayed combination; dialogue context encoding; dialogue management; disease diagnosis; Doc2vec; dual pointer network; encoder-decoder neural network; encodings; entity recognition; error assessment; error probability; FAQ classification; fixing ontologies; information extraction; knowledge base; Korean dataset; Korean syntax; language modeling; LaTeX decompilation; logic error; long short-term memory; long short-term memory network; LSTM; machine comprehension; medical specialist; multi-agent reinforcement learning; multi-level word embeddings; multi-turn chatbot; multilingual; multilingual transformers; multitask model; n/a; named entity recognition; natural language processing; Natural Language Processing (NLP); neural architecture search; neural language model; neural network; neural networks; news analysis; NLP; online social networks; ontologies; OntoNotes; open information extraction; paraphrase identification; partial match; polarity; primary healthcare; programming education; protein-protein interactions; quality metrics; question classification; quick fix; R-GCNs; recurrent neural networks; reinforce learning; relation extraction; reward shaping; rule-based; rumor detection; sememe prediction; sememes; sentence completion; sentence retrieval; sentiment analysis; sentiment classification; sequence similarity; speech-to-text; spoken natural language; structural information; text classification; text mining; text normalization; text summary; TF−ISF; tourism big data; toxic comments; transfer learning; user simulation; virtual medical assistant; WGAN-based response generation; word embedding; word embeddings; word ordering; word representation learning; word to vector; word2vec; XGA model; zero-shot learning
• Persona (resp. second.): MasalaGiovanni Luca; MinutoloAniello; PotaMarco; EspositoMassimo
• Sommario/riassunto: 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 neural systems, as well as on their potential or real applications in different domains.
• Altri titoli varianti: Natural Language Processing
• Titolo autorizzato: Natural Language Processing: Emerging Neural Approaches and Applications
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910566478103321
• Lo trovi qui: Univ. Federico II