Abstract
Scientific data constitutes a great asset. However, its volume is far bigger than any human can comprehend. Therefore, automatic analytical, search and indexing solutions are called for. In this paper we present the architecture and the data model of such a system. SONCA (Search based on ONtologies and Compound Analytics) is a platform to implement and exploit intelligent algorithms identifying relations between various types of objects (publications, inventions, scientists and institutions). The results of these algorithms can be used to build semantic search engines but also can be fed into further analytical algorithms in order to find even more associations.We also show experimental evaluation of the performance of SONCA. Its results are promising and we argue that SONCA’s architecture is robust.
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Grzegorowski, M., Pardel, P.W., Stawicki, S., Stencel, K. (2013). SONCA: Scalable Semantic Processing of Rapidly Growing Document Stores. In: Pechenizkiy, M., Wojciechowski, M. (eds) New Trends in Databases and Information Systems. Advances in Intelligent Systems and Computing, vol 185. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32518-2_9
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DOI: https://doi.org/10.1007/978-3-642-32518-2_9
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