Query-time reasoning in uncertain RDF knowledge bases with soft and hard rules

CEUR Workshop Proceedings

Volumn 884, Issue , 2012, Pages 15-20

  Nakashole, Ndapandula ^a   Sozio, Mauro ^b   Suchanek, Fabian ^a   Theobald, Martin ^a  

^a MAX PLANCK INSTITUTE FOR INFORMATICS   (Germany)

^b INSTITUT MINES TELECOM   (France)

Author keywords

Deductive Grounding; MaxSAT; Soft and Hard Rules; Uncertain RDF

Indexed keywords

AUTOMATIC CONSTRUCTION; CONSISTENCY CONSTRAINTS; EFFICIENT APPROXIMATION ALGORITHMS; EXTRACTION TECHNIQUES; MAX-SAT; SEMANTIC KNOWLEDGE; SOFT AND HARD RULES; UNCERTAIN RDF;

APPROXIMATION ALGORITHMS; DATA INTEGRATION; SEMANTICS;

SEMANTIC WEB;

EID: 84893157737     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (29)

1. N. Alon and J. Spencer. The Probabilistic Method. John Wiley, 1992.
2. L. Antova, C. Koch, and D. Olteanu. MayBMS: Managing incomplete information with probabilistic world-set decompositions. In ICDE, 2007.
3. K. R. Apt and M. H. van Emden. Contributions to the theory of logic programming. J. ACM, 29(3):841-862, 1982.
4. S. Auer, C. Bizer, G. Kobilarov, J. Lehmann, R. Cyganiak, and Z. G. Ives. DBpedia: a nucleus for a web of open data. In ISWC, pages 722-735, 2007.
5. J. Boulos, N. Dalvi, B. Mandhani, S. Mathur, C. Ré, and D. Suciu. MYSTIQ: a system for finding more answers by using probabilities. In SIGMOD, pages 891-893, 2005.
6. A. Carlson, J. Betteridge, R. C. Wang, E. R. H. Jr., and T. M. Mitchell. Coupled semi-supervised learning for information extraction. In WSDM, pages 101-110, 2010.
7. M.-W. Chang, L.-A. Ratinov, N. Rizzolo, and D. Roth. Learning and inference with constraints. In AAAI, pages 1513-1518, 2008.
8. M. X. Goemans and D. P. Williamson. New 3/4-approximation algorithms for the maximum satisfiability problem. SIAM J. Discr. Math., 7(4):656-666, 1994.
9. G. Gottlob and C. Papadimitriou. On the complexity of single-rule Datalog queries. Inf. Comput., 183:104-122, 2003.
10. Y. Guo, Z. Pan, and J. Heflin. LUBM: A benchmark for OWL knowledge base systems. Journal of Web Semantics, 3(2-3):158-182, 2005.
11. B. Jaumard and B. Simeone. On the complexity of the maximum satisfiability problem for Horn formulas. Information Processing Letters, 26(1):1-4, 1987.
12. D. S. Johnson. Approximation algorithms for combinatorial problems. Journal of Computer and System Sciences, pages 256-278, 1974.
13. H. Kautz, B. Selman, and Y. Jiang. A general stochastic approach to solving problems with hard and soft constraints. In The Satisfiability Problem: Theory and Applications, pages 573-586. American Mathematical Society, 1996.
14. T. Lukasiewicz. Probabilistic description logic programs. Int. J. Approx. Reasoning, 45(2):288-307, 2007.
15. T. Lukasiewicz and U. Straccia. Managing uncertainty and vagueness in description logics for the semantic web. J. of Web Semantics, (6):291-308,2008.
16. A. McCallum, K. Schultz, and S. Singh. FACTORIE: Probabilistic programming via imperatively defined factor graphs. In NPIS, pages 1249-1257. 2009.
17. T. Meiser, M. Dylla, and M. Theobald. Interactive reasoning in uncertain RDF knowledge bases. In CIKM, pages 2557-2560, 2011.
18. F. Niu, C. Ré, A. Doan, and J. W. Shavlik. Tuffy: Scaling up statistical inference in Markov Logic Networks using an RDBMS. PVLDB, 4(6):373-384, 2011.
19. R. Pichler, S. Rümmele, S. Szeider, and S. Woltran. Tractable answer-set programming with weight constraints: Bounded treewidth is not enough. In KR, 2010.
20. H. Poon, P. Domingos, and M. Sumner. A general method for reducing the complexity of relational inference and its application to MCMC. In AAAI, pages 1075-1080, 2008.
21. J. R. Quinlan. Learning logical definitions from relations. Machine Learning, 5:239-266, 1990.
22. L. D. Raedt, A. Kimmig, and H. Toivonen. ProbLog: A probabilistic Prolog and its application in link discovery. In IJCAI, pages 2462-2467, 2007.
23. M. Richardson and P. Domingos. Markov Logic Networks. Machine Learning, 62(1-2):107-136, 2006.
24. P. Singla and P. Domingos. Memory-efficient inference in relational domains. In AAAI, 2006.
25. F. M. Suchanek, G. Kasneci, and G. Weikum. Yago: A core of semantic knowledge. In WWW, 2007.
26. F. M. Suchanek, M. Sozio, and G. Weikum. SOFIE: A self-organizing framework for information extraction. In WWW, 2009.
27. M. Theobald, M. Sozio, F. M. Suchanek, and N. Nakashole. URDF: An efficient reasoning framework for uncertain knowledge bases with hard and soft rules. Technical report, Max-Planck-Institute for Informatics, 2010.
28. M. L. Wick, A. McCallum, and G. Miklau. Scalable probabilistic databases with factor graphs and MCMC. PVLDB, 3(1):794-804, 2010.
29. J. Widom. Trio: A system for integrated management of data, accuracy, and lineage. In CIDR, pages 262-276, 2005.