Authors
Mrinmaya Sachan, Avinava Dubey, Eric Xing
Publication date
2017
Conference
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
Pages
773 - 784
Publisher
Association for Computational Linguistics
Description
Textbooks are rich sources of information. Harvesting structured knowledge from textbooks is a key challenge in many educational applications. As a case study, we present an approach for harvesting structured axiomatic knowledge from math textbooks. Our approach uses rich contextual and typographical features extracted from raw textbooks. It leverages the redundancy and shared ordering across multiple textbooks to further refine the harvested axioms. These axioms are then parsed into rules that are used to improve the state-of-the-art in solving geometry problems.
Total citations
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