[1] |
C. Bobed, P. Maillot, P. Cellier, and S. Ferré. Data-driven assessment of structural evolution of RDF graphs. Semantic Web, page 1–23, April 2020. [ bib | DOI | http ] |
[2] |
P. Ristoski. Exploiting semantic web knowledge graphs in data mining. IOS Press, 2019. [ bib ] |
[3] |
X. Liu, K. Zhai, and W. Pedrycz. An improved association rules mining method. Expert Systems with Applications, 39(1):1362--1374, 2012. [ bib | DOI | http ] |
[4] |
K. Yan, W. Cui, and T. Zhao. Frequent Pattern-based Graph Exploration. In Proceedings of the 12th International Symposium on Visual Information Communication and Interaction. ACM Press, 2019. [ bib | DOI | http ] |
[5] |
C.S.R. Prabhu, A. S. Chivukula, A. Mogadala, R. Ghosh, and L.M. Jenila Livingston. Social Semantic Web Mining and Big Data Analytics. In Big Data Analytics: Systems, Algorithms, Applications, pages 217--231. Springer Singapore, 2019. [ bib | DOI | http ] |
[6] |
Chengqi Zhang and Shichao Zhang. Association rule mining: models and algorithms. Springer, 2003. [ bib ] |
[7] |
T. Herawan and M. M. Deris. A soft set approach for association rules mining. Knowledge-Based Systems, 24(1):186--195, February 2011. [ bib | DOI | http ] |
[8] |
G. Barisevičius, M. Coste, D. Geleta, D. Juric, M. Khodadadi, G. Stoilos, and I. Zaihrayeu. Supporting Digital Healthcare Services Using Semantic Web Technologies. In Lecture Notes in Computer Science, pages 291--306. Springer International Publishing, 2018. [ bib | DOI | http ] |
[9] |
T. Osadchiy, I. Poliakov, P. Olivier, M. Rowland, and E. Foster. Recommender system based on pairwise association rules. Expert Systems with Applications, 115:535--542, January 2019. [ bib | DOI | http ] |
[10] |
G. F. Pelap, C. F. Zucker, F. Gandon, and L. Polese. Web Semantic Technologies in Web Based Educational System Integration. In Lecture Notes in Business Information Processing, pages 170--194. Springer International Publishing, 2019. [ bib | DOI | http ] |
[11] |
M. A. Valle, G. A. Ruz, and R. Morrás. Market basket analysis: Complementing association rules with minimum spanning trees. Expert Systems with Applications, 97:146--162, May 2018. [ bib | DOI | http ] |
[12] |
H. Paulheim. Knowledge graph refinement: A survey of approaches and evaluation methods. Semantic Web, 8(3):489–508, December 2016. [ bib | DOI | http ] |
[13] |
S. Muggleton and L. d. Raedt. Inductive Logic Programming: Theory and methods. The Journal of Logic Programming, 19-20:629--679, 1994. [ bib | DOI | http ] |
[14] |
L. A. Galárraga, C. Teflioudi, K. Hose, and F. Suchanek. AMIE: association rule mining under incomplete evidence in ontological knowledge bases. In Proceedings of the 22nd international conference on World Wide Web. ACM Press, 2013. [ bib | DOI | http ] |
[15] |
L. Galárraga, C. Teflioudi, K. Hose, and F. M. Suchanek. Fast rule mining in ontological knowledge bases with AMIE+. The VLDB Journal, 24(6):707--730, July 2015. [ bib | DOI | http ] |
[16] |
B. T. Luong, S. Ruggieri, and F. Turini. Classification Rule Mining Supported by Ontology for Discrimination Discovery. In 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW). IEEE, 2016. [ bib | DOI | http ] |
[17] |
S. Vojíř, V. Zeman, J. Kuchař, and T. Kliegr. EasyMiner.eu: Web framework for interpretable machine learning based on rules and frequent itemsets. Knowledge-Based Systems, 150:111--115, June 2018. [ bib | DOI | http ] |
[18] |
J. S. Hong. A Methodology for Searching Frequent Pattern Using Graph-Mining Technique. Journal of Information Technology Applications and Management, 26(1):65--75, 2019. [ bib ] |
[19] |
A. V. V. Rao and B. E. Rambabu. Association rule mining using FPTree as directed acyclic graph. In IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM-2012), pages 202--207. IEEE, 2012. [ bib ] |
[20] |
V. Nebot and R. Berlanga. Finding association rules in semantic web data. Knowledge-Based Systems, 25(1):51--62, February 2012. [ bib | DOI | http ] |
[21] |
W.X. Wilcke, V. d. Boer, M.T.M. d. Kleijn, F.A.H. v. Harmelen, and H.J. Scholten. User-centric pattern mining on knowledge graphs: An archaeological case study. Journal of Web Semantics, 59:100486, 2019. [ bib | DOI | http ] |
[22] |
A. S. Heydari Yazdi and M. Kahani. A novel model for mining association rules from semantic web data. In 2014 Iranian Conference on Intelligent Systems (ICIS). IEEE, February 2014. [ bib | DOI | http ] |
[23] |
R. Ramezani, M. Saraee, and M. A. Nematbakhsh. MRAR: mining multi-relation association rules. Journal of Computing and Security, 1(2):133--158, 2014. [ bib ] |
[24] |
Z. Abedjan and F. Naumann. Improving RDF Data Through Association Rule Mining. Datenbank-Spektrum, 13(2):111--120, 2013. [ bib | DOI | http ] |
[25] |
E. Bytyçi, L. Ahmedi, and F. A. Lisi. Enrichment of association rules through exploitation of ontology properties healthcare case study. Procedia Computer Science, 113:360--367, 2017. [ bib | DOI | http ] |
[26] |
V. Narasimha, P. Kappara, R. Ichise, and O. Vyas. Liddm: A data mining system for linked data. In Workshop on Linked Data on the Web. CEUR Workshop Proceedings, page 108, 2011. [ bib ] |
[27] |
Christian Bizer, Tom Heath, and Tim Berners-Lee. Linked data: The story so far. In Semantic services, interoperability and web applications: emerging concepts, pages 205--227. IGI Global, 2011. [ bib | DOI ] |
[28] |
C. Bizer, T. Heath, and T. Berners-Lee. Linked Data - The Story So Far. International Journal on Semantic Web and Information Systems, 5(3):1--22, July 2009. [ bib | DOI | http ] |
[29] |
R. Ramezani, M. Saraee, and M. A. Nematbakhsh. Finding association rules in linked data, a centralization approach. In 2013 21st Iranian Conference on Electrical Engineering (ICEE). IEEE, May 2013. [ bib | DOI | http ] |
[30] |
M. A. Khan, G. A. Grimnes, and A. Dengel. Two pre-processing operators for improved learning from semanticweb data. In First RapidMiner Community Meeting And Conference (RCOMM 2010), 2010. [ bib ] |
[31] |
C. Kiefer, A. Bernstein, and A. Locher. Adding Data Mining Support to SPARQL Via Statistical Relational Learning Methods. In Lecture Notes in Computer Science, pages 478--492. Springer Berlin Heidelberg, 2008. [ bib | DOI | http ] |
[32] |
P. S.M Tsai and C. Chen. Mining interesting association rules from customer databases and transaction databases. Information Systems, 29(8):685--696, December 2004. [ bib | DOI | http ] |
[33] |
A. Patel and S. Jain. Present and future of semantic web technologies: a research statement. International Journal of Computers and Applications, pages 1--10, January 2019. [ bib | DOI | http ] |
[34] |
M. Barati, Q. Bai, and Q. Liu. Mining semantic association rules from RDF data. Knowledge-Based Systems, 133:183--196, 2017. [ bib | DOI | http ] |
|