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.

Format:

Book

Contributor:

Sun, Maosong, Editor.

Liu, Yang, Editor.

Che, Wanxiang, Editor.

Feng, Yang., Editor.

Qiu, Xipeng., Editor.

Rao, Gaoqi., Editor.

Chen, Yubo, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 13603

Lecture Notes in Artificial Intelligence, 2945-9141 ; 13603

Language:

English

Subjects (All):

Natural language processing (Computer science).

Computer engineering.

Computer networks.

Application software.

Natural Language Processing (NLP).

Computer Engineering and Networks.

Computer and Information Systems Applications.

Local Subjects:

Natural Language Processing (NLP).

Computer Engineering and Networks.

Computer and Information Systems Applications.

Physical Description:

1 online resource (XVII, 351 pages) : 83 illustrations, 76 illustrations in color.

Edition:

1st ed. 2022.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2022.

System Details:

text file PDF

Summary:

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.

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-3-031-18315-7

9783031183157

Access Restriction:

Restricted for use by site license.