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Semantic technology classification : a defence and security case study

Dirk Thorleuchter (UGent) and Dirk Van den Poel (UGent)
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Abstract
In the last years, an increasing collaboration between defense and (civil) security, especially in technological areas can be observed. Here, an approach that automatically extracts relationships among defense - based technologies and security - based technologies is introduced. Information about these relationships can be used as planning support to defense and security - based technological research planners specifically for collaboration decisions. This approach uses machine learning techniques as supervised learning methods and a multi-label text classification algorithm to identify related technologies in different technological lists or taxonomies. Additionally, a web mining approach is used to create training examples. Similarities are computed by use of Jaccard's coefficient and by use of the fuzzy alpha cut method. Further, this approach uses standard text mining methods to prepare unstructured textual information.

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Chicago
Thorleuchter, Dirk, and Dirk Van den Poel. 2011. “Semantic Technology Classification : a Defence and Security Case Study.” In 2011 International Conference on Uncertainty Reasoning and Knowledge Engineering (URKE), 36–39. Piscataway, NJ, USA: IEEE.
APA
Thorleuchter, D., & Van den Poel, D. (2011). Semantic technology classification : a defence and security case study. 2011 International Conference on Uncertainty Reasoning and Knowledge Engineering (URKE) (pp. 36–39). Presented at the 2011 International Conference on Uncertainty Reasoning and Knowledge Engineering (URKE), Piscataway, NJ, USA: IEEE.
Vancouver
1.
Thorleuchter D, Van den Poel D. Semantic technology classification : a defence and security case study. 2011 International Conference on Uncertainty Reasoning and Knowledge Engineering (URKE). Piscataway, NJ, USA: IEEE; 2011. p. 36–9.
MLA
Thorleuchter, Dirk, and Dirk Van den Poel. “Semantic Technology Classification : a Defence and Security Case Study.” 2011 International Conference on Uncertainty Reasoning and Knowledge Engineering (URKE). Piscataway, NJ, USA: IEEE, 2011. 36–39. Print.
@inproceedings{2039231,
  abstract     = {In the last years, an increasing collaboration between defense and (civil) security, especially in technological areas can be observed. Here, an approach that automatically extracts relationships among defense - based technologies and security - based technologies is introduced. Information about these relationships can be used as planning support to defense and security - based technological research planners specifically for collaboration decisions. This approach uses machine learning techniques as supervised learning methods and a multi-label text classification algorithm to identify related technologies in different technological lists or taxonomies. Additionally, a web mining approach is used to create training examples. Similarities are computed by use of Jaccard's coefficient and by use of the fuzzy alpha cut method. Further, this approach uses standard text mining methods to prepare unstructured textual information.},
  author       = {Thorleuchter, Dirk and Van den Poel, Dirk},
  booktitle    = {2011 International Conference on Uncertainty Reasoning and Knowledge Engineering (URKE)},
  isbn         = {9781424499854},
  language     = {eng},
  location     = {Bali, Indonesia},
  pages        = {36--39},
  publisher    = {IEEE},
  title        = {Semantic technology classification : a defence and security case study},
  url          = {http://dx.doi.org/10.1109/URKE.2011.6007833},
  year         = {2011},
}

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