Abstract
We present an architecture aimed at semantic search and synthesis of information acquired from the document repositories. The proposed framework is expected to provide domain knowledge interfaces enabling the internally implemented algorithms to identify relationships between documents, researchers, institutions, as well as concepts extracted from various types of knowledge bases. The framework should be scalable with respect to data volumes, diversity of analytic processes, and the speed of search. In this paper, we investigate these requirements for the case of medical publications gathered in PubMed.
This work was supported by the grant N N516 077837 from the Ministry of Science and Higher Education of the Republic of Poland and by the National Centre for Research and Development (NCBiR) under the grant SP/I/1/77065/10 by the Strategic scientific research and experimental development program “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information (SYNAT)”. We would like to acknowledge the whole SYNAT team, in particular: Marek Grzegorowski, Michał Kijowski, Marcin Kowalski, Adam Krasuski, and Krzysztof Stencel (co-creators of database model; Section ?), Kamil Herba, Grzegorz Jaśkiewicz, Michał Meina, Sinh Hoa Nguyen, and Marcin Szczuka (co-creators of experimental framework; Section ?), as well as Przemysław Pardel and Sebastian Stawicki (responsible for loading and parsing PubMed data). Special thanks go to Stanisława Bazan-Socha for her remarks on possible future usage of SONCA by biomedical experts.
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Ślęzak, D., Janusz, A., Świeboda, W., Nguyen, H.S., Bazan, J.G., Skowron, A. (2011). Semantic Analytics of PubMed Content. In: Holzinger, A., Simonic, KM. (eds) Information Quality in e-Health. USAB 2011. Lecture Notes in Computer Science, vol 7058. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25364-5_7
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