Workshop on Machine Reading

Co-located with K-Cap 2017

December 4, 2017


Machine Reading holds significant potential for automating knowledge capture, especially given the continuing improvements in natural-language processing technologies. Macro-reading techniques (skimming many documents) now enable collecting large databases of facts, while modern micro-reading techniques (comprehension of individual paragraphs) have proven effective at factoid question answering. In this workshop, participants will discuss ways to develop new capabilities in macro- and micro-reading to take these to the next level, in particular to extract useful representations of text (be they symbolic, neural, or a hybrid) that enable, for example, automated reasoning to answer non-trivial questions.

Topics

Machine Reading is very broad, encompassing many subdiscipines of AI, and its potential to help with knowledge capture is largely undeveloped. Here is a sample of the topics relevant to the workshop:

However, participants are encouraged to add to this list and to bring their own perspectives to the workshop.

Participation

The workshop will be organized as a working session with the aim of fostering discussion and sharing big ideas, even if they are untested. In this way, the workshop is not a traditional conference organized around the presentation of papers. If you would like to participate, please submit a short (1-2 page) position paper that describes your experience with machine reading research, if any, and your interests and plans for pursuing it. Submit your position paper by sending a PDF document to porter@cs.utexas.edu.

Schedule

Organizers

Program Committee

To Be Decided