Abstract
Huge amounts of data are generated by sensor readings, social media and databases. Such data introduce new challenges due to their volume and variety, and thus, new techniques are required for their utilization. We believe that reasoning can facilitate the extraction of new and useful knowledge. In particular, we may apply reasoning in order to make and support decisions, clean noisy data and derive high-level information from low-level input data. In this work we discuss the problem of large-scale reasoning over incomplete or inconsistent information, with an emphasis on nonmonotonic reasoning. We outline previous work, challenges and possible solutions, both over MapReduce and alternative high performance computing infrastructures.
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References
Fokoue, A., Felipe Meneguzzi, M.S., Pan, J.Z.: Querying linked ontological data through distributed summarization. In: Proc. of the 26th AAAI Conference on Artificial Intelligence (AAAI 2012) (2012)
Afrati, F.N., Ullman, J.D.: Optimizing Multiway Joins in a Map-Reduce Environment. IEEE Trans. Knowl. Data Eng. 23(9), 1282–1298 (2011)
Antoniou, G., Bikakis, A.: DR-Prolog: A System for Defeasible Reasoning with Rules and Ontologies on the Semantic Web. IEEE Trans. Knowl. Data Eng. 19(2), 233–245 (2007)
Antoniou, G., Williams, M.A.: Nonmonotonic reasoning. MIT Press (1997)
Bikakis, A., Antoniou, G.: Contextual Defeasible Logic and Its Application to Ambient Intelligence. IEEE Transactions on Systems, Man, and Cybernetics, Part A 41(4), 705–716 (2011)
Brass, S., Zukowski, U., Freitag, B.: Transformation-based bottom-up computation of the well-founded model (1997)
Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. In: Proc. of the 6th Conference on Symposium on Opearting Systems Design & Implementation, vol. 6, p. 10. USENIX Association, Berkeley (2004)
Eiter, T., Ianni, G., Lukasiewicz, T., Schindlauer, R.: Well-founded semantics for description logic programs in the semantic web. ACM Trans. Comput. Log. 12(2), 11 (2011)
Flouris, G., Konstantinidis, G., Antoniou, G., Christophides, V.: Formal foundations for RDF/S KB evolution. Knowl. Inf. Syst. 35(1), 153–191 (2013)
Gelfond, M.: Chapter 7 answer sets. In: van Harmelen, V.L., Porter, B. (eds.) Handbook of Knowledge Representation, vol. 3, pp. 285–316 (2008)
Harris, S., Lamb, N., Shadbolt, N.: 4store: The design and implementation of a clustered rdf store. In: 5th International Workshop on Scalable Semantic Web Knowledge Base Systems (SSWS 2009) (2009)
Hogan, A., Pan, J.Z., Polleres, A., Decker, S.: SAOR: Template Rule Optimisations for Distributed Reasoning over 1 Billion Linked Data Triples. In: Proc. of the 9th International Semantic Web Conference (ISWC 2010) (2010)
Knorr, M., Hitzler, P., Maier, F.: Reconciling OWL and Non-monotonic Rules for the Semantic Web. In: ECAI, pp. 474–479 (2012)
Konstantinidis, G., Flouris, G., Antoniou, G., Christophides, V.: A Formal Approach for RDF/S Ontology Evolution. In: ECAI, pp. 70–74 (2008)
Kotoulas, S., van Harmelen, F., Weaver, J.: KR and Reasoning on the Semantic Web: Web-Scale Reasoning (2011)
Kotoulas, S., Oren, E., van Harmelen, F.: Mind the data skew: distributed inferencing by speeddating in elastic regions. In: WWW, pp. 531–540 (2010)
Oren, E., Kotoulas, S., Anadiotis, G., Siebes, R., ten Teije, A., van Harmelen, F.: Marvin: Distributed reasoning over large-scale Semantic Web data. J. Web Sem. 7(4), 305–316 (2009)
Reiter, R.: A logic for default reasoning. Artif. Intell. 13(1-2), 81–132 (1980)
Ross, K.A.: The well-founded semantics for general logic programs. Journal of the ACM 38, 620–650 (1991)
Roussakis, Y., Flouris, G., Christophides, V.: Declarative Repairing Policies for Curated KBs. In: HDMS (2011)
Salvadores, M., Correndo, G., Harris, S., Gibbins, N., Shadbolt, N.: The design and implementation of minimal RDFS backward reasoning in 4store. In: Antoniou, G., Grobelnik, M., Simperl, E., Parsia, B., Plexousakis, D., De Leenheer, P., Pan, J. (eds.) ESWC 2011, Part II. LNCS, vol. 6644, pp. 139–153. Springer, Heidelberg (2011)
Salvadores, M., Correndo, G., Omitola, T., Gibbins, N., Harris, S., Shadbolt, N.: 4s-reasoner: Rdfs backward chained reasoning support in 4store. In: Web-scale Knowledge Representation, Retrieval, and Reasoning, Web-KR3 (September 2010)
Soma, R., Prasanna, V.K.: Parallel inferencing for owl knowledge bases. In: ICPP, pp. 75–82 (2008)
Tachmazidis, I., Antoniou, G.: Computing the stratified semantics of logic programs over big data through mass parallelization. In: Morgenstern, L., Stefaneas, P., Lévy, F., Wyner, A., Paschke, A. (eds.) RuleML 2013. LNCS, vol. 8035, pp. 188–202. Springer, Heidelberg (2013)
Tachmazidis, I., Antoniou, G., Flouris, G., Kotoulas, S.: Towards parallel nonmonotonic reasoning with billions of facts. In: KR (2012)
Tachmazidis, I., Antoniou, G., Flouris, G., Kotoulas, S., McCluskey, L.: Large-scale parallel stratified defeasible reasoning. In: ECAI, pp. 738–743 (2012)
Urbani, J., van Harmelen, F., Schlobach, S., Bal, H.: QueryPIE: Backward reasoning for OWL horst over very large knowledge bases. In: Aroyo, L., Welty, C., Alani, H., Taylor, J., Bernstein, A., Kagal, L., Noy, N., Blomqvist, E. (eds.) ISWC 2011, Part I. LNCS, vol. 7031, pp. 730–745. Springer, Heidelberg (2011)
Urbani, J., Kotoulas, S., Massen, J., van Harmelen, F., Bal, H.: Webpie: A web-scale parallel inference engine using mapreduce. Web Semantics: Science, Services and Agents on the World Wide Web 10 (2012)
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Antoniou, G., Pan, J.Z., Tachmazidis, I. (2014). Large-Scale Complex Reasoning with Semantics: Approaches and Challenges. In: Huang, Z., Liu, C., He, J., Huang, G. (eds) Web Information Systems Engineering – WISE 2013 Workshops. WISE 2013. Lecture Notes in Computer Science, vol 8182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54370-8_1
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