Sergei Nirenburg; Tim Oates
The goal of this symposium is to stimulate discussion and open exchange of ideas about two aspects of making texts semantically accessible to and processable by machines. The first, learning by reading, relates to automatically extracting machineunderstandable (machine-tractable) knowledge from text. The second, learning to read, is related to automating the process of knowledge extraction required to acquire and expand resources (for example, ontologies and lexicons) that facilitate learning by reading. There is a clear symbiotic relationship between these to aspects — expanding knowledge resources enables systems that extract knowledge from text to improve at that task over time and vice versa. Given significant diversity in topics, terminology, and writing styles, learning to read will be crucial to large-scale deployment of systems that learn by reading.