Abstract
Information systems knowledge bases often include inference rules. The continuous growth of the facts in the recent information systems environments has caused the exponential increase of rule bases sizes. Therefore, rule bases management becomes more and more difficult. Such a task should be automated and based on the extraction of dependencies between rules in order to have a better insight on their correct execution order and to detect conflicts between them. In this paper, we describe a rules dependency extraction approach for Semantic Web Rule Language (SWRL) rules. Our approach insures the automatic extraction of a rule dependency graph based on the semantics of their components. We evaluated our work by applying it to two different ontologies from medical and network security domains. We have implemented a prototype of our approach and we integrated it in a plug-in for Potégé-Owl editor.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
References
Baget, J.-F., Mugnier, M.-L., Thomazo, M.: Towards farsighted dependencies for existential rules. In: Rudolph, S., Gutierrez, C. (eds.) RR 2011. LNCS, vol. 6902, pp. 30–45. Springer, Heidelberg (2011). doi:10.1007/978-3-642-23580-1_4
Bak, J., Nowak, M., Jedrzejek, C.: Graph-based editor for SWRL rule bases. In: RuleML (2). Citeseer (2013)
Bouker, S., Saidi, R., Yahia, S.B., Nguifo, E.M.: Ranking and selecting association rules based on dominance relationship. In: 2012 IEEE 24th International Conference on Tools With Artificial Intelligence, vol. 1, pp. 658–665. IEEE (2012)
Brahim, M.B., Chaari, T., Jemaa, M.B., Jmaiel, M.: Semantic matching of web services security policies. In: 2012 7th International Conference on Risks and Security of Internet and Systems (CRiSIS), pp. 1–8. IEEE (2012)
Chevalier, J., Subercaze, J., Gravier, C., Laforest, F.: Incremental and directed rule-based inference on RDFS. In: Hartmann, S., Ma, H. (eds.) DEXA 2016. LNCS, vol. 9828, pp. 287–294. Springer, Heidelberg (2016). doi:10.1007/978-3-319-44406-2_22
Erdem, E., Erdem, Y., Erdogan, H., Öztok, U.: Finding answers and generating explanations for complex biomedical queries. In: AAAI (2011)
Fuertes-Olivera, P.A.: The function theory of lexicography and electronic dictionaries: wiktionary as a prototype of collective free multiple-language internet dictionary. In: Bergenholtz, H., Nielsen, S., Tarp, S. (eds.) Lexicography at a Crossroads: Dictionaries and Encyclopedias Today, Lexicographical Tools Tomorrow, pp. 99–134. Peter Lang, Bern (2009). ISBN: 978-3-03911-799-4
Gantayat, N., Das, R., Cherukuri, S.C.: Automated methodology comprised of supervised techniques to assist product selection. In: Recent Advances and Innovations in Engineering (ICRAIE), pp. 1–6. IEEE (2014)
Hassanpour, S., O’Connor, M., Das, A.: Axiomé: a tool for the elicitation and management of SWRL rules. In: Proceedings of the 6th International Conference on OWL: Experiences and Directions, vol. 529, pp. 204–207. CEUR-WS.org (2009)
Hassanpour, S., O’Connor, M.J., Das, A.K.: Exploration of SWRL rule bases through visualization, paraphrasing, and categorization of rules. In: Governatori, G., Hall, J., Paschke, A. (eds.) RuleML 2009. LNCS, vol. 5858, pp. 246–261. Springer, Heidelberg (2009). doi:10.1007/978-3-642-04985-9_23
Hassanpour, S., O’Connor, M.J., Das, A.K.: Visualizing logical dependencies in SWRL rule bases. In: Dean, M., Hall, J., Rotolo, A., Tabet, S. (eds.) RuleML 2010. LNCS, vol. 6403, pp. 259–272. Springer, Heidelberg (2010). doi:10.1007/978-3-642-16289-3_22
Hassanpour, S., O’Connor, M.J., Das, A.K.: Clustering rule bases using ontology-based similarity measures. Web Semant. Sci. Serv. Agents World Wide Web 25, 1–8 (2014)
Hirst, G., St-Onge, D.: Lexical chains as representations of context for the detection and correction of malapropisms. In: Fellbaum, C. (ed.) WordNet: An Electronic Lexical Database, vol. 305, pp. 305–332. MIT Press, Cambridge (1998)
Horrocks, I., Patel-Schneider, P.F., Boley, H., Tabet, S., Grosof, B., Dean, M., et al.: SWRL: a semantic web rule language combining OWL and ruleml. In: W3C Member submission, vol. 21, p. 79 (2004)
Katta, N., Alipourfard, O., Rexford, J., Walker, D.: Cacheflow: dependency-aware rule-caching for software-defined networks. In: Proceedings of the ACM Symposium on SDN Research (SOSR) (2016)
Krötzsch, M., Rudolph, S.: On the relationship of joint acyclicity and super-weak acyclicity. Technical report, Tech. rep. 3037, Institute AIFB, Karlsruhe Institute of Technology (2013). http://www.aifb.kit.edu/web/Techreport3013
Liu, Z., Feng, Z., Zhang, X., Wang, X., Rao, G.: RORS: enhanced rule-based owl reasoning on spark. arXiv preprint arXiv:1605.02824 (2016)
Lukasiewicz, T., Martinez, M.V., Simari, G.I.: Complexity of inconsistency-tolerant query answering in datalog+/–. In: Meersman, R., Panetto, H., Dillon, T., Eder, J., Bellahsene, Z., Ritter, N., Leenheer, P., Dou, D. (eds.) OTM 2013. LNCS, vol. 8185, pp. 488–500. Springer, Heidelberg (2013). doi:10.1007/978-3-642-41030-7_35
McGuinness, D.L., Van Harmelen, F., et al.: OWL web ontology language overview. In: W3C recommendation, vol. 10(10), p. 2004 (2004)
Miller, G.A.: Wordnet: a lexical database for English. Commun. ACM 38(11), 39–41 (1995)
O’Connor, M.: Swrltab (2008)
Panchenko, A., et al.: Similarity measures for semantic relation extraction. Ph.D. thesis, UCL (2013)
Rivolli, A., Orlando, J.P., Moreira, D.A.: An analysis of rules-based systems to improve swrl tools. In: Proceedings of the ICEIS (4), pp. 191–194 (2011)
Sap, A.: See your business clearly. SAP BusinessObjects Dashboards. http://www.sap.com/uk/solutions/sapbusinessobjects/large/business-intelligence/dashboards/sapbusinessobjects-dashboards/index.epx
Seipel, D.: Knowledge engineering for hybrid deductive databases. In: 29nd Workshop on (Constraint) Logic Programming (WLP 2015), p. 66 (2015)
Singh, P., Lin, T., Mueller, E.T., Lim, G., Perkins, T., Zhu, W.L.: Open mind common sense: knowledge acquisition from the general public. In: Meersman, R., Tari, Z. (eds.) OTM 2002. LNCS, vol. 2519, pp. 1223–1237. Springer, Heidelberg (2002). doi:10.1007/3-540-36124-3_77
Speer, R., Havasi, C.: Conceptnet 5: a large semantic network for relational knowledge. In: Gurevych, I., Kim, J. (eds.) The People’s Web Meets NLP, pp. 161–176. Springer, Heidelberg (2013)
Vossen, P.: From wordnet to eurowordnet to the global wordnet grid: anchoring languages to universal meaning. Guest lecture, Language Engineering Applications, 26 February 2009
Yang, F., Xing, Y., Sun, H., Sun, T., Chen, S.: An ontology-based semantic similarity measure considering multi-inheritance in biomedicine. Math. Probl. Eng. 2015, 1–9 (2015)
Zacharias, V., Borgi, I.: Exploiting usage data for the visualization of rule bases. In: Proceedings of the 3rd International Semantic Web User Interaction Workshop SWUI. Citeseer (2006)
Zetta, T., Kontopoulos, E., Bassiliades, N.: S 2 red: a semantic web rule editor (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Boujelben, A., Chaari, T., Amous, I. (2017). Towards Better SWRL Rules Dependency Extraction. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_77
Download citation
DOI: https://doi.org/10.1007/978-3-319-53480-0_77
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-53479-4
Online ISBN: 978-3-319-53480-0
eBook Packages: EngineeringEngineering (R0)