Special Issue on Language Technology and Knowledge Graphs
摘要截稿:
全文截稿: 2019-09-30
影响因子: 2.238
期刊难度:
CCF分类: B类
中科院JCR分区:
• 大类 : 计算机科学 - 2区
• 小类 : 计算机:人工智能 - 2区
• 小类 : 计算机:信息系统 - 2区
• 小类 : 计算机:软件工程 - 2区
Overview
Language understanding and knowledge engineering are among the most active research and development areas due to the proliferation of big data. This special issue on Language Technology and Knowledge Graphs is devoted to gather and present innovative research, systems and applications that address the challenges in the broad areas of language and knowledge intelligence, presenting a platform for researchers to share their recent observations and achievements in the field. Special topics for this special issue include but are not limited to:
1. Textual Entailment and Knowledge
Textual entailment
Fact checking
Fake news detection
Argumentation mining
2. Knowledge-Guided NLP
Question answering and reading comprehension
Dialogue systems
Information Retrieval
Multilinguality
Recommender systems
Machine Translation
Knowledge-Guided Deep Learning
Complex knowledge-driven Information Extraction tasks e.g., relation extraction, event extraction
Methods and metrics for evaluation of semantic annotations with respect to ontologies
Knowledge-driven entity disambiguation and resolution
3. Contextual Knowledge Graphs and Language Technology
Extracting and modelling temporally bounded information
Dealing with culturally-aware information
Handling domain specificity of information
4. Information Extraction for Knowledge Graphs
Extraction from unstructured versus semi-structured textual sources (e.g. tables)
Dealing with the imperfections of Information Extraction techniques in the Semantic Web setting and their impact
Multi-source or multilingual Information Extraction for ontology population
Information extraction subtasks (e.g., terminology extraction, relation extraction, coreference resolution) for the Semantic Web
Methods and metrics for evaluation of Information Extraction for the Semantic Web
5. Applications and Architectures
Knowledge-based Information Extraction for specific domains and applications, e.g. business analytics, healthcare and biomedicine, cultural heritage etc.
Information Extraction for social media mining
Scalability of tools and resources
Platforms and architectures for automatic and semi-automatic semantic annotation
Tools and methodologies for building and managing complex processing workflows