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Prerequisites for Fuzzy Inference on Raw Text Using Semantic Reasoner
2025-09-27
There are a lot of knowledge in the Web, but there is no technological way to extract them. The bulk of knowledge is embedded in texts, and machine text processing is so inefficient that it is necessary to use Semantic Web technologies [1]. Working with ontologies (part of the Semantic Web) is convenient, but the process of creating ontologies is still more of a manual work than an automatic process. This paper proposes to generate IF..THEN rules from raw texts (from sentences) in the Web, and then perform logical inference based on these rules. Moreover, semantic processing is proposed to be applied to the IF part and the THEN part, and not to the entire raw text, generating an ontology from it. This method of generating rules and logical inference is being implemented in the Keyword Search Engine Enriched by Expert System Features [2], which will allow us to obtain expert assessments from many useful texts in the Web.
Ссылка для цитирования:
Верходуб О. А. 2025. Prerequisites for Fuzzy Inference on Raw Text Using Semantic Reasoner. PREPRINTS.RU. https://doi.org/10.24108/preprints-3113756
Список литературы
1. [1] J. Davis, R. Studer, P. Warren, “Semantic Web Technologies Trends and Research in On-tology-based Systems,” John Wiley & Sons Ltd, Chichester, 2006.
2. [2] O. Verhodubs, Keyword Search Engine Enriched by Expert System Features, 2020.
3. [3] O. Verhodubs, Experiments of Rule Extraction from Raw Text, 2021.
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10. [9] https://www.cs.princeton.edu/courses/archive/fall07/cos436/HIDDEN/Knapp/fuzzy004.htm [Accessed: 26.09.2025]
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12. [11] O. Verhodubs, Ontology as a source for rule generation, 2014.
13. [12] O. Verhodubs, Generation of Rules from the Relational Database Structure, 2023.
