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The main contributions are related to performance improvement: (1) the top-k approach, which addresses the problem of combinatorial explosion often resulting from a hand-set minimum support threshold, (2) a grammar that allows to define fine-grained patterns reducing the size of the search space, and (3) a faster projection binding reducing the number of repetitive calculations. Other enhancements include the possibility to mine across multiple graphs, the support for discretization of continuous values, and the selection of the most representative rules using proven rule pruning and clustering algorithms. Benchmarks show reductions in mining time of up to several orders of magnitude compared to AMIE+. An open-source implementation is available under the name RDFRules at https:\/\/github.com\/propi\/rdfrules.<\/jats:p>","DOI":"10.3233\/sw-200413","type":"journal-article","created":{"date-parts":[[2021,1,26]],"date-time":"2021-01-26T12:48:18Z","timestamp":1611665298000},"page":"569-602","source":"Crossref","is-referenced-by-count":5,"title":["RDFRules: Making RDF rule mining easier and even more efficient"],"prefix":"10.1177","volume":"12","author":[{"given":"V\u00e1clav","family":"Zeman","sequence":"first","affiliation":[{"name":"Department of Information and Knowledge Engineering, Faculty of Informatics and Statistics, Prague University of Economics and Business, n\u00e1m W Churchilla 4, 13067, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tom\u00e1\u0161","family":"Kliegr","sequence":"additional","affiliation":[{"name":"Department of Information and Knowledge Engineering, Faculty of Informatics and Statistics, Prague University of Economics and Business, n\u00e1m W Churchilla 4, 13067, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vojt\u011bch","family":"Sv\u00e1tek","sequence":"additional","affiliation":[{"name":"Department of Information and Knowledge Engineering, Faculty of Informatics and Statistics, Prague University of Economics and Business, n\u00e1m W Churchilla 4, 13067, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/SW-200413_ref1","doi-asserted-by":"publisher","DOI":"10.1145\/170036.170072"},{"key":"10.3233\/SW-200413_ref2","unstructured":"R.\u00a0Agrawal, R.\u00a0Srikant et al., Fast algorithms for mining association rules in large databases, in: Proc. 20th Int. 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