|About this Abstract
||MS&T22: Materials Science & Technology
||Curricular Innovations and Continuous Improvement of Academic Programs (and Satisfying ABET along the Way): The Elizabeth Judson Memorial Symposium
||Assisting Curation of Open-Source Textbook with Natural Language Processing
||Amit K. Verma, Benjamin M Glaser, Robin Kuo, Jason Zhang, Nicholas David, Zhisong Zhang, Emma Strubell, Anthony D Rollett
|On-Site Speaker (Planned)
||Amit K. Verma
Natural Language Processing (NLP) provides a host of solutions to map the knowledge space for the open-source textbook and a pathway to continuously update this mapping. In this direction, we are working on two key ideas: 1) data retrieval; & 2) recognition systems for identifying key concepts and their dependencies, from published literature. The first aims to address the lack of open-access experimental data for various machine learning activities, while the second aim to encode the semantics of the domain for bridging various heterogeneous data sources. In this talk, we will share our vision for the open-source textbook, and where we see NLP tools can support the curation process. Further, we will expand on the tools mentioned, with specific examples to support our vision.