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Tags: named entity recognition

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Publications

2022

  1. C. Hanks, M. Maiden, P. Ranade, T. Finin, and A. Joshi, "CyberEnt: Extracting Domain Specific Entities from Cybersecurity Text", InProceedings, Mid-Atlantic Student Colloquium on Speech, Language and Learning, April 2022, 1042 downloads.
  2. C. Hanks and M. Maiden, "CyberEnt: A Cybersecurity Domain Specific Dataset for Named Entity Recognition", Misc, UMBC Undergraduate Research and Creative Achievement Day, April 2022, 640 downloads.

2020

  1. S. Dasgupta, A. Piplai, A. Kotal, and A. Joshi, "A Comparative Study of Deep Learning based Named Entity Recognition Algorithms for Cybersecurity", InProceedings, IEEE International Conference on Big Data 2020, December 2020, 1190 downloads.
  2. C. H. Song, D. Lawrie, T. Finin, and J. Mayfield, "Gazetteer Generation for Neural Named Entity Recognition", InProceedings, Proceedings of the 33rd International FLAIRS Conference, May 2020, 937 downloads.
  3. C. H. Song, D. Lawrie, and T. Finin, "Improving Neural Named Entity Recognition with Gazetteers", Article, arXiv:2003.03072, March 2020, 1588 downloads.

2019

  1. O. M. Singh, A. Padia, and A. Joshi, "Named Entity Recognition for Nepali Language", Article, arXiv:1908.05828 [cs.CL], August 2019, 905 downloads.

2015

  1. T. Finin, D. Lawrie, P. McNamee, J. Mayfield, D. Oard, N. Peng, N. Gao, Y. Lin, J. MacKin, and T. Dowd, "HLTCOE Participation in TAC KBP 2015: Cold Start and TEDL", InProceedings, Eighth Text Analysis Conference, November 2015, 988 downloads.

2013

  1. R. Lal, "Information Extraction of Security related entities and concepts from unstructured text.", MastersThesis, University of Maryland Baltimore County, May 2013, 2380 downloads.

2012

  1. v. Stoyanov, J. Mayfield, T. Xu, D. Oard, D. Lawrie, T. Oates, and T. Finin, "A Context-Aware Approach to Entity Linking", InProceedings, Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction, June 2012, 3196 downloads.

2010

  1. W. Murnane, "Improving Accuracy of Named Entity Recognition on Social Media Data", MastersThesis, University of Maryland, Baltimore County, August 2010, 5772 downloads, 3 citations.
  2. T. Finin, W. Murnane, A. Karandikar, N. Keller, J. Martineau, and M. Dredze, "Annotating named entities in Twitter data with crowdsourcing", InProceedings, Proceedings of the NAACL Workshop on Creating Speech and Text Language Data With Amazon's Mechanical Turk, June 2010, 3168 downloads.

Dataset

  1. Annotations of Cybersecurity blogs and articles

Presentation

  1. Extracting Cybersecurity related entities, terms and concepts from text.

Poster

  1. Improving Accuracy of Named Entity Recognition on Social Media Data

Old Events

  1. Information Extraction of Security related entities and concepts from unstructured text
    April 1, 2013
  2. Machine aided human translation - An automated system for transcribing dictated document translations
    October 8, 2010
  3. Improving Accuracy of Named Entity Recognition on Social Media Data
    May 19, 2010
  4. Collecting user annotations using Amazon Mechanical Turk and CrowdFlower
    March 9, 2010