Introduction
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.
Call for paper
Submission 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:
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advances and new directions in NLP
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methods of active learning for guiding machine readers to useful content
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methods for (dis)confirming content derived from text
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extracting content from tables and diagrams
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integrating extracted information into a knowledge base
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hybrids methods that combine "deep NLP" and symbolic logic
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ways that macro reading might inform micro reading, and vice versa
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Important Date
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Dec 04
2017
Conference Date
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Dec 04 2017
Registration deadline
Contact Information
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