Analogy-making as perception: a computer model
Analogy-making as perception: a computer model
Understanding language understanding: computational models of reading
Understanding language understanding: computational models of reading
A theory of questions and question asking
Understanding language understanding
Creativity in reading: understanding novel concepts
Understanding language understanding
On the intersection of story understanding and learning
Understanding language understanding
Tell Me a Story: A New Look at Real and Arfificial Memory: A New Look at Real and Artificial MEM
Tell Me a Story: A New Look at Real and Arfificial Memory: A New Look at Real and Artificial MEM
Dynamic memories: analysis of an integrated comprehension and episodic memory retrieval model
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
A connectionist model of human reading
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Text representation by a computational model of reading
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
| Hi-index | 0.01 |
Anthropocentrism of computational systems is totally justified when the task concerns to natural language. Computational linguistics systems usually rely on mathematical and statistical formalisms, which are efficient and useful but far from human procedures and therefore not so skilled. The presented work proposes a computational model of natural language reading, called cognitive reading indexing model (CRIM), inspired by some aspects of human cognition, trying to become as psychologically plausible as possible. The model relies on a semantic neural network and it produces nets of activated concepts as text representations. The experimental evaluation shows that the system is suitable to model human reading, and it provides a framework to validate and assess hypothesis concerning reading from other cognitive science fields.