Abstract
One of the main tasks in the integration of information systems is to provide relevant retrieval of information consolidated from heterogeneous sources. In the field of inorganic chemistry and materials science, set-theoretic methods of searching for relevant information are known. They ensure the construction of a sufficiently high-quality response to user requests. However, the problem of quantifying evaluation of information search relevance in this subject area remains open. This paper proposes an approach to quantifying evaluation of the relevance of information retrieval in integrated systems on inorganic substances and materials properties by introducing the relevance graph built on chemical objects. A “chemical similarity” metric and measure are proposed and their properties are discussed.
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References
Dudarev, V.A., Kiselyova, N.N., Temkin, I.O.: Relevance Evaluation of Information Retrieval in the Integration of Information Systems on Inorganic Substances Properties. Selected Papers of the XXI International Conference on Data Analytics and Management in Data Intensive Domains (DAMDID/RCDL 2019). Kazan, Russia, 15–18 October 2019. CEUR Workshop Proceedings, vol. 2523, pp. 348–357. http://ceur-ws.org/Vol-2523/paper34.pdf
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Acknowledgement
This work was partially supported by the Russian Foundation for Basic Research (project no. 18-07-00080) and the State task № 075-00746-19-00.
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Dudarev, V.A., Kiselyova, N.N., Temkin, I.O. (2020). On Information Search Measures and Metrics Within Integration of Information Systems on Inorganic Substances Properties. In: Elizarov, A., Novikov, B., Stupnikov, S. (eds) Data Analytics and Management in Data Intensive Domains. DAMDID/RCDL 2019. Communications in Computer and Information Science, vol 1223. Springer, Cham. https://doi.org/10.1007/978-3-030-51913-1_4
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DOI: https://doi.org/10.1007/978-3-030-51913-1_4
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