Preface

• How can FCA support AI activities such as knowledge processing (knowledge discov- ery, knowledge representation and reasoning), learning (clustering, pattern and data mining),

Particularly, the use of representation learning for link prediction tasks requires train and test sampling, non-edge sampling, and in many cases selection of edge embedding methods

This edition of the AIC Workshop had a special focus on work related to problems concerning cognitively-inspired methods of Knowledge Representation and Reasoning, Knowledge

This includes theoretical and experimental on-going works about novel representation models, learning algorithms, and knowledge-based methodologies for emerging trends and

Social Practice Theory could help in analysing and understanding how such learning processes take place for different actors by studying the actual performance

• How can FCA support AI activities such as knowledge processing (knowledge discov- ery, knowledge representation and reasoning), learning (clustering, pattern and data mining),

• How can FCA support AI activities such as knowledge processing (knowledge discov- ery, knowledge representation and reasoning), learning (clustering, pattern and data mining),

Well- established software engineering methods and approaches (e.g., iterative development processes, issue tracking systems) could provide additional value to systems engineering