Mars Target Encyclopedia: Rock and Soil Composition Extracted From the Literature

Authors

  • Kiri Wagstaff California Institute of Technology
  • Raymond Francis California Institute of Technology
  • Thamme Gowda California Institute of Technology; Information Sciences Institute, University of Southern California
  • You Lu California Institute of Technology
  • Ellen Riloff University of Utah
  • Karanjeet Singh California Institute of Technology
  • Nina Lanza Los Alamos National Laboratory

Keywords:

machine learning, information extraction, planetary science

Abstract

We have constructed an information extraction system called the Mars Target Encyclopedia that takes in planetary science publications and extracts scientific knowledge about target compositions. The extracted knowledge is stored in a searchable database that can greatly accelerate the ability of scientists to compare new discoveries with what is already known. To date, we have applied this system to ~6000 documents and achieved 41-56% precision in the extracted information.

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Published

2018-04-27

How to Cite

Wagstaff, K., Francis, R., Gowda, T., Lu, Y., Riloff, E., Singh, K., & Lanza, N. (2018). Mars Target Encyclopedia: Rock and Soil Composition Extracted From the Literature. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/11412