When dealing with narrative texts, a system must possess a strong domain theory, and especially knowledge about situations occurring in the world. Otherwise the system must envisa...
This paper describes an on-going effort to investigate problems and approaches for achieving Web-service-based, dynamic and collaborative e-learning. In this work, a Learning Cont...
To address the problem of algorithm selection for the classification task, we equip a relational case base with new similarity measures that are able to cope with multirelational ...
Parallel and distributed information processing systems play an increasingly important role in artificial intelligence and computer science. In this article an approach to learnin...
We present context-sensitive Multiple Task Learning, or csMTL as a method of inductive transfer. It uses additional contextual inputs along with other input features when learning ...