Abstract
The paper explores whether the semantic context is good enough to cope with ever increasing number of available resources in different repositories including the web. Here a problem of identifying authors of scientific papers is used as an example. A set of problem still do arise in case we apply exclusively the semantic context. Fortunately contextual semantic can be used to derive more information required to separate ambiguous cases. Semantic tags, well-structured documents and available databases of articles do provide a possibility to be more context-aware. Under the context we use co-authors names, references and headers to extract key-words and identify the subject. The real complexity of the considering problem comes from the dynamical behaviour of authors as they can change the topic of the research in the next paper. As the final judge the paper proposes applying words usage patterns analysis. Final the contextual intelligence engine is described.
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References
T. Berners-Lee, J., Hendler, and O. Lassila, “The semantic web”, Scientific American, 2001.
M. H. Coen, “Design principles for intelligent environments”, Proceedings of AAAI/IAAI, 1998, pp. 547–554.
A. Roy, S. K. D. Bhaumik, A. Bhattacharya, K. Basu, D.J. Cook, and S.K. Das, “Location aware resource management in smart homes”, Proceedings of First IEEE International Conference on Pervasive Computing and Communications (PerCom’03), 2003, pp. 481-488.
H. Chen, T. Finin, and A. Joshi, “Semantic Web in the context broker architecture”, Proceedings of the 2nd IEEE Annual Conference on Pervasive Computing and Communications (PerCom '04), 2004, pp. 277–286.
P. Chang, A. Gul, “Towards Context-Aware Web Applications”, 7th IFIP International Conference on Distributed Applications and Interoperable Systems (DAIS), Springer, vol. 4531, 2007, pp. 239–252.
W.Y. Lum, and F.C.M. Lau, “A context-aware decision engine for content adaptation”, IEEE Pervasive Computing, vol. 1 (3), 2002, pp. 41–49.
J. Pascoe, “Adding Generic Contextual Capabilities to Wearable Computers”, Proc. 2nd Int’l Symp. Wearable Computers, IEEE CS Press, Los Alamitos, Calif., 1998, pp. 92–99.
J.E. Hirsch, ”An index to quantify an individual's scientific research output”, Proceedings of the National Academy of Science, vol. 102 (46), 2005, pp. 16569-16572.
D. Kumlander, “Soft Biometrical Students Identification Method for e-Learning”, Proceedings of Advances in Computer and Information Sciences and Engineering, Springer, Netherlands, 2008, pp. 114 – 118.
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Kumlander, D. (2010). Contextual Semantic: A Context-aware Approach for Semantic Web Based Data Extraction from Scientific Articles. In: Sobh, T., Elleithy, K. (eds) Innovations in Computing Sciences and Software Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9112-3_40
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DOI: https://doi.org/10.1007/978-90-481-9112-3_40
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