Abstract
This article is a continuation of research work started with an idea of semantic compression. As authors proved that semantic compression is viable concept for English, they decided to focus on potential applications. An algorithm is presented that employing WiSENet allows for knowledge acquisition with flexible rules that yield high precision results. Detailed discussion is given with description of devised algorithm, usage examples and results of experiments.
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Ceglarek, D., Haniewicz, K., Rutkowski, W. (2011). Towards Knowledge Acquisition with WiSENet. In: Nguyen, N.T., Trawiński, B., Jung, J.J. (eds) New Challenges for Intelligent Information and Database Systems. Studies in Computational Intelligence, vol 351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19953-0_8
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DOI: https://doi.org/10.1007/978-3-642-19953-0_8
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