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Ralph Grishman

Professor of Computer Science

    1967 …2019
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    Fingerprint Weighted list of dominant concepts in the researcher's publications (titles and abstracts).

    Semantics Engineering & Materials Science
    Linguistics Engineering & Materials Science
    Syntactics Engineering & Materials Science
    event Social Sciences
    language Social Sciences
    Labeling Engineering & Materials Science
    Processing Engineering & Materials Science
    evaluation Social Sciences

    Network Recent external collaboration on country level. Dive into details by clicking on the dots.

    Research Output 1967 2019

    Twenty-five years of information extraction

    Grishman, R., Jan 1 2019, (Accepted/In press) In : Natural Language Engineering.

    Research output: Contribution to journalArticle

    information content
    Neural networks
    neural network
    Processing
    evaluation

    Graph convolutional networks with argument-aware pooling for event detection

    Nguyen, T. H. & Grishman, R., Jan 1 2018, 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. AAAI press, p. 5900-5907 8 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Neural networks
    Syntactics
    Convolution
    Experiments

    Including new patterns to improve event extraction systems

    Cao, K., Li, X., Ma, W. & Grishman, R., Jan 1 2018, Proceedings of the 31st International Florida Artificial Intelligence Research Society Conference, FLAIRS 2018. Rus, V. & Brawner, K. (eds.). AAAI press, p. 487-492 6 p. (Proceedings of the 31st International Florida Artificial Intelligence Research Society Conference, FLAIRS 2018).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Active learning based named entity recognition and its application in natural language coverless information hiding

    Sun, H., Grishman, R. & Wang, Y., 2017, In : Journal of Internet Technology. 18, 2, p. 443-451 9 p.

    Research output: Contribution to journalArticle

    Labeling
    Sampling
    Problem-Based Learning
    Big data

    Distributed representation learning for knowledge graphs with entity descriptions

    Fan, M., Zhou, Q., Zheng, T. F. & Grishman, R., Apr 15 2016, (Accepted/In press) In : Pattern Recognition Letters.

    Research output: Contribution to journalArticle

    Knowledge representation
    Deep neural networks