Abstract
The paper considers the task of building the ontological structure of knowledge in the intelligent assistant systems to reduce the structural and semantic conflicts in the process of searching, accumulation, and processing of information objects in the Internet. The authors develop the semantic net providing the integrated representation of knowledge on user preferences, semantic images of the Internet resource, and search domain in the ontological model. To solve the problem, we propose a method for cluster analysis of the Internet-object structure. This allows us to divide the vector space of the features into semantic clusters with the constraints on the hidden patterns features revealing the content risks. To carry out the experiments on a test set of search queries, we developed a search module for the intelligent assistant system. The estimated relevance coefficient of “query-resource” is 60% higher than manually formed user preferences in popular search systems.
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The reported study was funded by RFBR according to the research project № 18-29-22019.
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Bova, V.V., Kravchenko, Y.A., Rodzin, S.I., Kuliev, E.V. (2021). Simulation of the Semantic Network of Knowledge Representation in Intelligent Assistant Systems Based on Ontological Approach. In: Singh, P.K., Veselov, G., Pljonkin, A., Kumar, Y., Paprzycki, M., Zachinyaev, Y. (eds) Futuristic Trends in Network and Communication Technologies. FTNCT 2020. Communications in Computer and Information Science, vol 1396. Springer, Singapore. https://doi.org/10.1007/978-981-16-1483-5_22
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DOI: https://doi.org/10.1007/978-981-16-1483-5_22
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