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Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 11 Similar Profiles
Reinforcement learning Engineering & Materials Science
Taxonomies Engineering & Materials Science
Labeling Engineering & Materials Science
Semantics Engineering & Materials Science
Learning systems Engineering & Materials Science

Research Output 2015 2018

  • 6 Conference contribution
  • 1 Poster
  • 1 Article

A Deep Dive into Word Sense Disambiguation with LSTM

Le, M. N., Postma, M. C., Urbani, J. & Vossen, P. T. J. M., 21 Aug 2018

Research output: Contribution to ConferencePosterAcademic

Deep Dive into Word Sense Disambiguation with LSTM

Le, M. N., Postma, M. C., Urbani, J. & Vossen, P. T. J. M., 2018, Proceedings of the International Conference on Computational Linguistics (COLING 2018).

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Open Access

Neural Models of Selectional Preferences for Implicit Semantic Role Labeling

Le, M. N. & Fokkens, A. S., 2018, Proceedings of the 11th edition of the Language Resources and Evaluation Conference (LREC2018). p. 3062 6 p.

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Open Access
Labeling
Semantics
Learning systems

Tackling Error Propagation through Reinforcement Learning: A Case of Greedy Dependency Parsing

Le, M. N. & Fokkens, A. S., Apr 2017, Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics. Valencia, Spain, Vol. 1, p. 677-687 10 p.

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Open Access
File
Reinforcement learning

Word Sense Disambiguation with LSTM: Do We Really Need 100 Billion Words?

Le, M., Postma, M. & Urbani, J., 9 Dec 2017, In : arXiv.org.

Research output: Contribution to JournalArticleAcademic