ISSN: 2666-6510

AI Open is a freely accessible platform to share actionable knowledge and forward-thinking perspectives on the theory of artificial intelligence and its applications. The journal welcomes research ar...

AI Open is a freely accessible platform to share actionable knowledge and forward-thinking perspectives on the theory of artificial intelligence and its applications. The journal welcomes research articles, review papers, perspectives, short communications and technical notes on all aspects of artificial intelligence and its applications.

Topics covered include, but are not limited to:

  • Deep learning and representation learning
  • Graph theory and graph mining
  • Constraints, satisfiability, and search
  • Knowledge representation, reasoning, and logic
  • Machine learning and data mining
  • Knowledge graph and applications
  • Agent-based and multi-agent systems
  • Web and knowledge-based information systems
  • Natural language processing
  • Image processing and analysis
  • Uncertainty
  • Brain-based Learning
  • Implicit Cognition and Learning

Human Brain Research:

  • Hot topics in human brain-related health/diseases/social behavior
  • Brain Connectivity and network modeling
  • Brain intelligence paradigms
  • Neuro-informatics
  • Neuroimaging
  • Learning and memory
  • Cognition and behavior
  • health data analysis and statistics
  • Neuroimmunology
  • Sleep behavior
  • Deep brain stimulation

Advances and challenges in conversational recommender systems: A survey

Neural, symbolic and neural-symbolic reasoning on knowledge graphs

Robustness of deep learning models on graphs: A survey

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1. Graph neural networks: A review of methods and applications

2. Neural machine translation: A review of methods, resources, and tools

3. Pre-Trained Models: Past, Present and Future

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Call for Papers

Special issue on AI and law

Special Issue on Women in AI

Special Issue on Social Media Processing

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News

New NLP model improves stock market predictions

A group of researchers at the Research Center for Social Computing and Information Retrieval at China’s Harbin Institute of Technology have constructed a model that can synthesise these multiple data sources and the various forms of data they contain. Study results, published in the KeAi journal AI Open, show that their model achieves a higher AUC (area under the precision-recall curve) score than existing models.

Beijing Academy of Artificial Intelligence (BAAI) Conference 2021

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