Natural Language Processing and Chinese Computing : 10th CCF International Conference, NLPCC 2021, Qingdao, China, October 13-17, 2021, Proceedings, Part II / edited by Lu Wang, Yansong Feng, Yu Hong, Ruifang He.

Format:

Book

Contributor:

Wang, Lu, Editor.

Feng, Yansong, Editor.

Hong, Yu, Editor.

He, Ruifang, Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 13029

Lecture Notes in Artificial Intelligence ; 13029

Language:

English

Subjects (All):

Artificial intelligence.

Natural language processing (Computer science).

Data mining.

Information storage and retrieval systems.

Artificial Intelligence.

Natural Language Processing (NLP).

Data Mining and Knowledge Discovery.

Information Storage and Retrieval.

Local Subjects:

Artificial Intelligence.

Natural Language Processing (NLP).

Data Mining and Knowledge Discovery.

Information Storage and Retrieval.

Physical Description:

1 online resource (XXXVI, 630 pages) : 330 illustrations, 146 illustrations in color.

Edition:

1st ed. 2021.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2021.

System Details:

text file PDF

Summary:

This two-volume set of LNAI 13028 and LNAI 13029 constitutes the refereed proceedings of the 10th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2021, held in Qingdao, China, in October 2021. The 66 full papers, 23 poster papers, and 27 workshop papers presented were carefully reviewed and selected from 446 submissions. They are organized in the following areas: Fundamentals of NLP; Machine Translation and Multilinguality; Machine Learning for NLP; Information Extraction and Knowledge Graph; Summarization and Generation; Question Answering; Dialogue Systems; Social Media and Sentiment Analysis; NLP Applications and Text Mining; and Multimodality and Explainability.

Contents:

Posters - Fundamentals of NLP

Syntax and Coherence - The Effect on Automatic Argument Quality Assessment

ExperienceGen 1.0: A Text Generation Challenge Which Requires Deduction and Induction Ability

Machine Translation and Multilinguality

SynXLM-R: Syntax-enhanced XLM-R in Translation Quality Estimation

Machine Learning for NLP

Memetic Federated Learning for Biomedical Natural Language Processing

Information Extraction and Knowledge Graph

Event Argument Extraction via a Distance-Sensitive Graph Convolutional Network

Exploit Vague Relation: An Augmented Temporal Relation Corpus and Evaluation

Searching Effective Transformer for Seq2Seq Keyphrase Generation

Prerequisite Learning with Pre-trained Language and Graph Embedding Models

Summarization and Generation

Variational Autoencoder with Interactive Attention for Affective Text Generation

CUSTOM: Aspect-Oriented Product Summarization for E-Commerce

Question Answering

FABERT: A Feature Aggregation BERT-Based Model for Document Reranking

Generating Relevant, Correct and Fluent Answers in Natural Answer Generation

GeoCQA: A Large-scale Geography-Domain Chinese Question Answering Dataset from Examination

Dialogue Systems

Generating Informative Dialogue Responses with Keywords-Guided Networks

Zero-Shot Deployment for Cross-Lingual Dialogue System

MultiWOZ 2.3: A multi-domain task-oriented dialogue dataset enhanced with annotation corrections and co-reference annotation

EmoDialoGPT: Enhancing DialoGPT with Emotion

Social Media and Sentiment Analysis

BERT-based Meta-learning Approach with Looking Back for Sentiment Analysis of Literary Book Reviews

ISWR: an Implicit Sentiment Words Recognition Model Based on Sentiment Propagation

An Aspect-Centralized Graph Convolutional Network for Aspect-based Sentiment Classification

NLP Applications and Text Mining

Capturing Global Informativeness in Open Domain Keyphrase Extraction

Background Semantic Information Improves VerbalMetaphor Identification

Multimodality and Explainability

Towards unifying the explainability evaluation methods for NLP

Explainable AI Workshop

Detecting Covariate Drift with Explanations

A Data-Centric Approach Towards Deducing Bias in Artificial Intelligence Systems for Textual Contexts

Student Workshop

Enhancing Model Robustness via Lexical Distilling

Multi-stage Multi-modal Pre-training for Video Representation

Nested Causality Extraction on Traffic Accident Texts as Question Answering

Evaluation Workshop

MSDF: A General Open-Domain Multi-Skill Dialog Framework

RoKGDS: A Robust Knowledge Grounded Dialog System

Enhanced Few-shot Learning with Multiple-Pattern-Exploiting Training

BIT-Event at NLPCC-2021 Task 3: Subevent Identification via Adversarial Training

Few-shot Learning for Chinese NLP tasks

When Few-shot Learning Meets Large-scale Knowledge-enhanced Pre-training: Alibaba at FewCLUE

TKB²ert: Two-stage Knowledge Infused Behavioral Fine-tuned BERT

A Unified Information Extraction System Based on Role Recognition and Combination

A Simple but Effective System for Multi-format Information Extraction

A Hierarchical Sequence Labeling Model for Argument Pair Extraction

Distant finetuning with discourse relations for stance classification

The Solution of Xiaomi AI Lab to the 2021 Language and Intelligence Challenge: Multi-Format Information Extraction Task

A Unified Platform for Information Extraction with Two-stage Process

Overview of the NLPCC 2021 Shared Task: AutoIE2

Task 1 - Argumentative Text Understanding for AI Debater (AIDebater)

Two Stage Learning for Argument Pairs Extraction

Overview of Argumentative Text Understanding for AI Debater Challenge

ACE: A Context-Enhanced model for Interactive Argument Pair Identification

Context-Aware and Data-Augmented Transformer for Interactive Argument Pair Identification

ARGUABLY @ AI Debater-NLPCC 2021 Task 3: Argument Pair Extraction from Peer Review and Rebuttals

Sentence Rewriting for Fine-Tuned Model Based on Dictionary: Taking the Track 1 of NLPCC 2021 Argumentative Text Understanding for AI Debater as an Example

Knowledge Enhanced transformers System for Claim Stance Classification.

Other Format:

Printed edition:

ISBN:

978-3-030-88483-3

9783030884833

Access Restriction:

Restricted for use by site license.