Chinese Computational Linguistics : 21st China National Conference, CCL 2022, Nanchang, China, October 14–16, 2022, Proceedings / / edited by Maosong Sun, Yang Liu, Wanxiang Che, Yang Feng, Xipeng Qiu, Gaoqi Rao, Yubo Chen

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
• Edizione: 1st ed. 2022.
• Descrizione fisica: 1 online resource (354 pages)
• Disciplina: 006.35
• Soggetto topico: Natural language processing (Computer science); Computer engineering; Computer networks; Application software; Natural Language Processing (NLP); Computer Engineering and Networks; Computer and Information Systems Applications
• Persona (resp. second.): SunMaosong
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Linguistics and Cognitive Science -- Discourse Markers as the Classificatory Factors of Speech Acts -- Fundamental Theory and Methods of Computational Linguistics -- DIFM: An effective deep interaction and fusion model for sentence matching -- ConIsI: A Contrastive Framework with Inter-sentence Interaction for Self-supervised Sentence Representation -- Information Retrieval, Dialogue and Question Answering -- Data Synthesis and Iterative Refinement for Neural Semantic Parsing without Annotated Logical Forms -- EventBERT: Incorporating Event-based Semantics for Natural Language Understanding -- An Exploration of Prompt-Based Zero-Shot Relation Extraction Method -- Abstains from Prediction: Towards Robust Relation Extraction in Real World -- Using Extracted Emotion Cause to Improve Content-Relevance for Empathetic Conversation Generation -- Text Generation and Summarization -- To Adapt or to Fine-tune: A Case Study on Abstractive Summarization -- Knowledge Graph and Information Extraction -- MRC-based Medical NER with Multi-task Learning and Multi-strategies -- A Multi-Gate Encoder for Joint Entity and Relation Extraction -- Improving Event Temporal Relation Classification via Auxiliary Label-Aware Contrastive Learning -- Machine Translation and Multilingual Information Processing -- Towards Making the Most of Pre-trained Translation Model for Quality Estimation -- Supervised Contrastive Learning for Cross-lingual Transfer Learning -- Minority Language Information Processing -- Interactive Mongolian Question Answer Matching Model Based on Attention Mechanism in the Law Domain -- Language Resource and Evaluation -- TCM-SD: A Benchmark for Probing Syndrome Differentiation via Natural Language Processing -- COMPILING: A Benchmark Dataset for Chinese Complexity Controllable Definition Generation -- NLP Applications -- Can We Really Trust Explanations? Evaluating the Stability of Feature Attribution Explanation Methods via Adversarial Attack -- Dynamic Negative Example Construction for Grammatical Error Correction using Contrastive Learning -- SPACL: Shared-Private Architecture based on Contrastive Learning for Multi-domain Text Classification -- Low-Resource Named Entity Recognition Based on Multi-hop Dependency Trigger -- Fundamental Analysis based Neural Network for Stock Movement Prediction.
• Sommario/riassunto: This book constitutes the proceedings of the 21st China National Conference on Computational Linguistics, CCL 2022, held in Nanchang, China, in October 2022. The 22 full English-language papers in this volume were carefully reviewed and selected from 293 Chinese and English submissions. The conference papers are categorized into the following topical sub-headings: Linguistics and Cognitive Science; Fundamental Theory and Methods of Computational Linguistics; Information Retrieval, Dialogue and Question Answering; Text Generation and Summarization; Knowledge Graph and Information Extraction; Machine Translation and Multilingual Information Processing; Minority Language Information Processing; Language Resource and Evaluation; NLP Applications.
• Titolo autorizzato: Chinese Computational Linguistics
• ISBN: 3-031-18315-0
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910616209003321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Artificial Intelligence, . 2945-9141 ; ; 13603