Abstract
The paper presents a new hybrid schema matching algorithm: Semantic Structure Matching Recommendation Algorithm (SSRMA). SSRMA is able to discover lexical correspondences without breaking the structural ones — it is capable of rejecting trivial lexical similarities, if the structural context suggests that a given matching is inadequate. The algorithm enables achieving results that are comparable to those obtained by means of state-of-the-art schema matching solutions. The presented method involves an adaptable pre-processing and flexible internal data representation, which allows to use a variety of auxiliary data (e.g., textual corpora) and to increase the accuracy of semantic matches accommodated in a given domain. In order to increase the mapping quality, the method allows to extend the input data by auxiliary information that may have the form of ontologies or textual corpora.
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Szwabe, A., Jachnik, A., Figaj, A., Blinkiewicz, M. (2011). Semantic Structure Matching Recommendation Algorithm. In: Dziech, A., Czyżewski, A. (eds) Multimedia Communications, Services and Security. MCSS 2011. Communications in Computer and Information Science, vol 149. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21512-4_9
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DOI: https://doi.org/10.1007/978-3-642-21512-4_9
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