Semantic Web efforts aim to bring the WWW to a state in which all its content can be interpreted by machines; the ultimate goal being a machine-processable Web of Knowledge. We strongly believe that adding a mechanism to extract and compute concepts from the Semantic Web will help to achieve this vision. However, there are a number of open questions that need to be answered first. In this paper we will establish partial answers to the following questions: 1) Is it feasible to obtain data from the Web (instantaneously) and compute formal concepts without a considerable overhead; 2) have data sets, found on the Web, distinct properties and, if so, how do these properties affect the performance of concept discovery algorithms; and 3) do state-of-the-art concept discovery algorithms scale wrt. the number of data objects found on the Web? © 2012 Springer-Verlag.
CITATION STYLE
Kirchberg, M., Leonardi, E., Tan, Y. S., Link, S., Ko, R. K. L., & Lee, B. S. (2012). Formal concept discovery in semantic web data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7278 LNAI, pp. 164–179). https://doi.org/10.1007/978-3-642-29892-9_18
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