Métais / Meziane / Horacek Natural Language Processing and Information Systems

26th International Conference on Applications of Natural Language to Information Systems, NLDB 2021, Saarbrücken, Germany, June 23–25, 2021, Proceedings
1. Auflage 2021
ISBN: 978-3-030-80599-9
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 386 Seiten, eBook

Reihe: Information Systems and Applications, incl. Internet/Web, and HCI

This book constitutes the refereed proceedings of the 26th International Conference on Applications of Natural Language to Information Systems, NLDB 2021, held online in July 2021.The 19 full papers and 14 short papers were carefully reviewed and selected from 82 submissions. The papers are organized in the following topical sections: role of learning; methodological approaches; semantic relations; classification; sentiment analysis; social media; linking documents; multimodality; applications.

Zielgruppe

Research

Autoren/Hrsg.

Métais, Elisabeth

Meziane, Farid

Horacek, Helmut

Kapetanios, Epaminondas

Inhaltsverzeichnis

The Role of Learning.-
You can’t Learn what’s not there: Self Supervised Learning and the Poverty of the Stimulus.- Scaling Federated Learning for Fine-tuning of Large Language Models.- Overcoming the Knowledge Bottleneck Using Lifelong Learning by Social Agents.-
Methodological Approaches.-
Word Embedding-based Topic Similarity Measures.- Mixture Variational Autoencoder of Boltzmann Machines for Text Processing.- A Modular Approach for Romanian-English Speech Translation.- NumER: A Fine-grained Numeral Entity Recognition Dataset.- Cross-Domain Transfer of Generative Explanations using Text-to-Text Models.-
Semantic Relations.-
Virus Causes Flu: Identifying Causality in the Biomedical Domain using an Ensemble Approach with Target-specific Semantic Embeddings.- Multilevel Entity-Informed Business Relation Extraction.- The Importance of Character-Level Information in an Event Detection Model.-
Classification.-
Sequence-based Word Embeddings for Effective TextClassification.- BERT-Capsule Model for Cyberbullying Detection in Code-Mixed Indian Languages.- Multiword Expression Features for Automatic Hate Speech Detection.- Semantic Text Segment Classification of Structured Technical Content.- On the Generalization of Figurative Language Detection: the Case of Irony and Sarcasm.- Extracting Facts from Case Rulings through Paragraph Segmentation of Judicial Decisions.- Detection of Misinformation about COVID-19 in Brazilian Portuguese WhatsApp Messages.-
Sentiment Analysis.-
Multi-Step Transfer Learning for Sentiment Analysis.- Improving Sentiment Classification in Low Resource Bengali Language Utilizing Cross-lingual Self-supervised Learning.- Human Language Comprehension in Aspect Phrase Extraction with Importance Weighting.- Exploring Summarization to Enhance Headline Stance Detection.- Predicting Vaccine Hesitancy and Vaccine Sentiment using Topic Modeling and Evolutionary Optimization.- Sentiment Progression based Searching and Indexing of Literary Textual Artefacts.-
Social Media.-
Argument Mining in Tweets: Comparing Crowd and Expert Annotations for Automated Claim and Evidence Detection.- Authorship Attribution using Capsule-based Fusion Approach.- On the Explainability of Automatic Predictions of Mental Disorders from Social Media Data.-
Linking Documents.-
Using Document Embeddings for Background Linking of News Articles.- Let’s Summarize Scientific Documents! A Clustering-based Approach via Citation Context.-
Multimodality.-
Cross-Active Connection for Image-Text Multimodal Feature Fusion.- Profiling Fake News Spreaders: Personality and Visual Information Matter 315.-
Applications.-
Comparing MultiLingual and Multiple MonoLingual Models for Intent Classification and Slot Filling.- Automated Retrieval of Graphical User Interface Prototypes from Natural Language Requirements.