Abstract
There is an increasing interest in automating creation of semantic structures, especially topic maps, by taking advantage of existing, structured information resources. This paper gives a preview of the most popular method — based on RDF triples, and suggests a way to automate topic map creation from unstructured information sources. The method can be applied in information systems development domain when analyzing vast unstructured data repositories in preparation for system design, or when migrating large amounts of unstructured data from legacy systems. There are two innovative methods presented in the paper — Term Crawling (TC) and Clustering History Projection (CHP), which are used in order to build a topic map based on free text documents downloaded from the Internet. A sample tool, which uses described techniques, has been implemented. The preliminary results that have been achieved on the test collection are presented in concluding sections of the article.
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Abramowicz, W., Kaczmarek, T., Kowalkiewicz, M. (2004). Automatic Topic Map Creation Using Term Crawling and Clustering Hierarchy Projection. In: Linger, H., et al. Constructing the Infrastructure for the Knowledge Economy. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-4852-9_42
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DOI: https://doi.org/10.1007/978-1-4757-4852-9_42
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