Ontology enrichment by discovering multi-relational association rules from ontological knowledge bases

Author:

d'Amato Claudia1,Staab Steffen2,Tettamanzi Andrea G. B.3,Minh Tran Duc3,Gandon Fabien4

Affiliation:

1. University of Bari, Italy

2. University of Southampton, UK & University of Koblenz-Landau, Germany

3. Univ. Nice Sophia Antipolis, France

4. INRIA Sophia Antipolis, France

Funder

This work fulfills the objectives of the PON 02 00563 3489339 project PUGLIA@SERVICE - Internet-based Service Engineering enabling Smart Territory structural development funded by the Italian Ministry of University and Research (MIUR).

Publisher

ACM

Cited by 15 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. INK: Knowledge graph representation for efficient and performant rule mining;Semantic Web;2023-10-02

2. Rule Learning over Knowledge Graphs with Genetic Logic Programming;2022 IEEE 38th International Conference on Data Engineering (ICDE);2022-05

3. Fragmented Knowledge Clustering method based on SOM;International Journal of System Assurance Engineering and Management;2022-01-31

4. RDFRules: Making RDF rule mining easier and even more efficient;Semantic Web;2021-06-17

5. Ontology for Smart Viticulture: Integrating Inference Rules Based on Sensor Data;Lecture Notes in Computer Science;2020

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