Abstract
This work describes the idea of an adaptive semantic layer for large-scale databases, allowing to effectively handling a large amount of information. This effect is reached by providing an opportunity to search information on the basis of generalized concepts, or in other words, linguistic descriptions. These concepts are formulated by the user in natural language, and modelled by fuzzy sets, defined on the universum of the significances of the attributes of the database. After adjustment of user’s concepts based on search results, we have “personalized semantics” for all terms which particular person uses for communications with database (for example, “young person” will be different for teenager and for old person; “good restaurant” will be different for people with different income, age, etc.).
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Notes
- 1.
Following [6], we associate semantics of the terms (words) with membership functions.
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Ryjov, A. (2018). Personalization and Optimization of Information Retrieval: Adaptive Semantic Layer Approach. In: Zadeh, L., Yager, R., Shahbazova, S., Reformat, M., Kreinovich, V. (eds) Recent Developments and the New Direction in Soft-Computing Foundations and Applications. Studies in Fuzziness and Soft Computing, vol 361. Springer, Cham. https://doi.org/10.1007/978-3-319-75408-6_2
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