Abstract
This paper studies semantic retrieval method based on rule-based reasoning under support of ontology. In the support of ontology knowledge base, this system faces ontology structure-based metadata, according to related concepts and reasoning rules, looks for implication relationship and digs out implicit information. We extract reasoning rules from semantic relationship of audit information, and present Smallest Connected Subgraph Generation Algorithm, Connected Componets Generation Algorithm and Connected Componets Matching Rules Algorithm; these three algorithms are in solving problems in the process of reasoning, implement the reasoning function. Through case analysis, we verify the application probability of these algorithms in audit information resource retrieval.
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Liu, G., Feng, L., Liu, Y., Wang, Z. (2011). Research on Rule-Based Reasoning Methods Oriented on Information Resource Ontology. In: Wang, Y., Li, T. (eds) Foundations of Intelligent Systems. Advances in Intelligent and Soft Computing, vol 122. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25664-6_13
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DOI: https://doi.org/10.1007/978-3-642-25664-6_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25663-9
Online ISBN: 978-3-642-25664-6
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