Andrew McCallum

Andrew McCallum is a professor in the computer science department at University of Massachusetts Amherst. His primary specialties are in machine learning, natural language processing, information extraction, information integration, and social network analysis. Provided by Wikipedia
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  1. 1
    Teachers’ constructions of creativity in secondary English : who gets to be creative in class?

    Teachers’ constructions of creativity in secondary English : who gets to be creative in class? by McCallum, Andrew F.

    Published 2018
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    Thesis
  2. 2
    Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning

    Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning by Kim, Edward, Huang, Kevin Joon-Ming, Saunders, Adam, McCallum, Andrew, Ceder, Gerbrand, Olivetti, Elsa A.

    Published 2021
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    Article
  3. 3
    MS-Mentions: Consistently Annotating Entity Mentions in Materials Science Procedural Text

    MS-Mentions: Consistently Annotating Entity Mentions in Materials Science Procedural Text by O’Gorman, Tim, Jensen, Zach, Mysore, Sheshera, Huang, Kevin, Mahbub, Rubayyat, Olivetti, Elsa, McCallum, Andrew

    Published 2022
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    Article
  4. 4
    Machine-learned and codified synthesis parameters of oxide materials

    Machine-learned and codified synthesis parameters of oxide materials by Strubell, Emma, Saunders, Adam, McCallum, Andrew, Olivetti, Elsa, Kim, Edward, Huang, Kevin Joon-Ming, Tomala, Alex, Matthews, Sara C.

    Published 2018
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    Article
  5. 5
    The materials science procedural text corpus: Annotating materials synthesis procedures with shallow semantic structures

    The materials science procedural text corpus: Annotating materials synthesis procedures with shallow semantic structures by Mysore, Sheshera, Jensen, Zach, Kim, Edward, Huang, Kevin Joon-Ming, Chang, Haw-Shiuan, Strubell, Emma, Flanigan, Jeffrey, McCallum, Andrew, Olivetti, Elsa A.

    Published 2021
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    Article
  6. 6
    Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks

    Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks by Kim, Edward, Jensen, Zach, van Grootel, Alexander, Huang, Kevin, Staib, Matthew, Mysore, Sheshera, Chang, Haw-Shiuan, Strubell, Emma, McCallum, Andrew, Jegelka, Stefanie, Olivetti, Elsa

    Published 2021
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    Article
  7. 7
    Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks

    Inorganic Materials Synthesis Planning with Literature-Trained Neural Networks by Kim, Edward, Jensen, Zach, van Grootel, Alexander, Huang, Kevin Joon-Ming, Staib, Matthew, Mysore, Sheshera, Chang, Haw-Shiuan, Strubell, Emma, McCallum, Andrew, Jegelka, Stefanie Sabrina, Olivetti, Elsa A.

    Published 2022
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    Article

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