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Search for Appropriate Textual Information Sources
Adam Albert, Marie Duží, Marek Menšík, Miroslav Pajr, Vojtěch Patschka
227 - 246
10.3233/FAIA200832
Research Article
Frontiers in Artificial Intelligence and Applications
Volume 333: Information Modelling and Knowledge Bases XXXII
Abstract

In this paper, we deal with the support in the search for appropriate textual sources. Users ask for an atomic concept that is explicated using machine learning methods applied to different textual sources. Next, we deal with the so-obtained explications to provide even more useful information. To this end, we apply the method of computing association rules. The method is one of the data-mining methods used for information retrieval. Our background theory is the system of Transparent Intensional Logic (TIL); all the concepts are formalised as TIL constructions.

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