Abstract
Large amounts of data in modern information systems, such as the World Wide Web, require innovative information retrieval techniques to effectively satisfy users’ information need. A promising approach is to exploit document semantics in the IR process. For this purpose, high-quality semantic metadata is needed. This paper introduces a method to automatically create semantic metadata by using ontologically enhanced versions of common information extraction methods, such as named entity recognition and coreference resolution. Furthermore, this work also proposes the application of ontology-specific heuristic rules to further improve the quality of generated metadata. The results of our method was evaluated using a small test collection.
This work was partially funded by the VICODI (EU-IST-2001-37534), DIP (FP6-507483), and IMAGINATION (FP6-034626) EU IST projects.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11914853_71.
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Yoldas, Ü., Nagypál, G. (2006). Ontology Supported Automatic Generation of High-Quality Semantic Metadata. In: Meersman, R., Tari, Z. (eds) On the Move to Meaningful Internet Systems 2006: CoopIS, DOA, GADA, and ODBASE. OTM 2006. Lecture Notes in Computer Science, vol 4275. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11914853_48
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DOI: https://doi.org/10.1007/11914853_48
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