Learning semantic definitions of online information sources

Journal of Artificial Intelligence Research

Volumn 30, Issue , 2007, Pages 1-50

  Carman, Mark James ^a   Knoblock, Craig A ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

FINANCIAL DATA PROCESSING; INFORMATION RETRIEVAL; MATHEMATICAL MODELS; ONLINE SYSTEMS; PROBLEM SOLVING; WEB SERVICES;

INFORMATION SOURCES; WEB SOURCES;

LEARNING SYSTEMS;

EID: 38349193107     PISSN: None     EISSN: 10769757     Source Type: Journal    
DOI: 10.1613/jair.2205     Document Type: Article

References (38)

1. Afrati, F. N., Li, C., & Mitra, P. (2004). On containment of conjunctive queries using arithmetic comparisions. In 9th International Conference on Extending Database Technology (EDBT 2004) Heraklion-Crete, Greece.
2. Arens, Y., Knoblock, C. A., & Shen, W.-M. (1996). Query reformulation for dynamic information integration. Journal of Intelligent Information Systems - Special Issue on Intelligent Information Integration, 6(2/3), 99-130.
3. Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The semantic web. Scientific American, 284(5), 34-43.
4. Bilenko, M., Mooney, R. J., Cohen, W. W., Ravikumar, P., & Fienberg, S. E. (2003). Adaptive name matching in information integration.. IEEE Intelligent Systems, 18(5), 16-23.
5. Cameron-Jones, R. M., & Quinlan, J. R. (1994). Efficient top-down induction of logic programs. SIGART Bulletin, 5(1), 33-42.
6. Carman, M. J., & Knoblock, C. A. (2007). Learning semantic descriptions of web information sources. In Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI-07) Hyderabad, India.
7. Chandra, A. K., & Merlin, P. M. (1977). Optimal implementation of conjunctive queries in relational data bases. In Proceedings of the 9th ACM Symposium on Theory of Computing (STOC), pp. 77-90 Boulder, Colorado.
8. Dhamanka, R., Lee, Y., Doan, A., Halevy, A., & Domingos, P. (2004). imap: Discovering complex semantic matches between database schemas. In SIGMOD '04: Proceedings of the 2004 ACM SIGMOD International Conference on Management of Data.
9. Dong, X., Halevy, A. Y., Madhavan, J., Nemes, E., & Zhang, J. (2004). Simlarity search for web services. In Proceedings of VLDB.
10. Duschka, O. M. (1997). Query Planning and Optimization in Information Integration. Ph.D. thesis, Department of Computer Science, Stanford University.
11. Garcia-Molina, H., Hammer, J., Ireland, K., Papakonstantinou, Y., Ullman, J., & Widom, J. (1995). Integrating and accessing heterogeneous information sources in tsimmis. In Proceedings of the AAAI Symposium on Information Gathering, pp. 61-64.
12. Heß, A., & Kushmerick, N. (2003). Learning to attach semantic metadata to web services. In 2nd International Semantic Web Conference (ISWC).
13. Heß, A., & Kushmerick, N. (2004). Iterative ensemble classification for relational data: A case study of semantic web services. In 15th European Conference on Machine Learning (ECML2004) Pisa, Italy. Springer.
14. Knoblock, C. A., Minton, S., Ambite, J. L., Ashish, N., Muslea, I., Philpot, A., & Tejada, S. (2001). The ariadne approach to web-based information integration. International Journal of Cooperative Information Systems, 10(1-2), 145-169.
15. Lerman, K., Plangprasopchok, A., & Knoblock, C. A. (2006). Automatically labeling data used by web services. In Proceedings of the 21st National Conference on Artificial Intelligence (AAAI).
16. Levy, A. Y. (2000). Logic-based techniques in data integration. In Minker, J. (Ed.), Logic-Based Artificial Intelligence. Kluwer Publishers.
17. Levy, A. Y., Mendelzon, A. O., Sagiv, Y., & Srivastava, D. (1995). Answering queries using views. In Proceedings of the 14th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, pp. 95-104 San Jose, Calif.
18. Markov, Z., & Marinchev, I. (2000). Metric-based inductive learning using semantic height functions. In Proceedings of the 11th European Conference on Machine Learning (ECML 2000). Springer.
19. Martin, D., Paolucci, M., McIlraith, S., Burstein, M., McDermott, D., McGuinness, D., Parsia, B., Payne, T., Sabou, M., Solanki, M., Srinivasan, N., & Sycara, K. (2004). Bringing semantics to web services: The owl-s approach. In Proceedings of the First International Workshop on Semantic Web Services and Web Process Composition (SWSWPC 2004).
20. Muggleton, S., & Feng, C. (1990). Efficient induction of logic programs. In Proceedings of the 1st Conference on Algorithmic Learning Theory.
21. Muggleton, S. (1995). Inverse entailment and Progol. New Generation Computing, Special issue on Inductive Logic Programming, 13(3-4), 245-286.
22. Nédellec, C., Rouveirol, C., Adé, H., Bergadano, F., & Tausend, B. (1996). Declarative bias in ILP. In De Raedt, L. (Ed.), Advances in Inductive Logic Programming, pp. 82-103. IOS Press.
23. Pazzani, M. J., & Kibler, D. F. (1992). The utility of knowledge in inductive learning. Machine Learning, 9, 57-94.
24. Perkowitz, M., & Etzioni, O. (1995). Category translation: Learning to understand information on the internet. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI-95).
25. Perkowitz, M., Doorenbos, R. B., Etzioni, O., & Weld, D. S. (1997). Learning to understand information on the internet: An example-based approach. Journal of Intelligent Information Systems, 8(2), 133-153.
26. Pottinger, R., & Halevy, A. Y. (2001). Minicon: A scalable algorithm for answering queries using views. VLDB Journal, 10(2-3).
27. Quinlan, J. R., & Cameron-Jones, R. M. (1993). FOIL: A midterm report. In Machine Learning: ECML-93, European Conference on Machine Learning, Proceedings, Vol. 667, pp. 3-20. Springer-Verlag.
28. Rahm, E., & Bernstein, P. (2001). A survey of approaches to automatic schema matching. VLDB Journal, 10(4).
29. Richards, B. L., & Mooney, R. J. (1992). Learning relations by pathfinding. In National Conference on Artificial Intelligence, pp. 50-55.
30. Roman, D., Keller, U., Lausen, H., de Bruijn, J., Lara, R., Stollberg, M., Polleres, A., Feier, C., Bussler, C., & Fensel, D. (2005). Web service modeling ontology. Applied Ontology, 1(1), 77-106.
31. Ullman, J. D. (1989). Principles of Database and Knowledge-Base Systems, Vol. 2. Computer Science Press, Rockville, Maryland.
32. Weber, I., Tausend, B., & Stahl, I. (1995). Language series revisited: The complexity of hypothesis spaces in ILP. In Proceedings of the 8th European Conference on Machine Learning, Vol. 912, pp. 360-363. Springer-Verlag.
33. Widom, J. (1995). Research problems in data warehousing. In CIKM '95: Proceedings of the fourth International Conference on Information and Knowledge Management, pp. 25-30. ACM Press.
34. Wiederhold, G. (1992). Mediators in the architecture of future information systems. Computer, 25(3), 38-49.
35. Wiederhold, G. (Ed.). (1996). Intelligent Integration of Information. Kluwer Academic Publishers, Boston MA.
36. Winkler, W. (1999). The state of record linkage and current research problems. Tech. rep., Statistical Research Division, U.S. Bureau of the Census, Washington, DC.
37. Yan, L. L., Miller, R. J., Haas, L. M., & Fagin, R. (2001). Data-driven understanding and refinement of schema mappings. In SIGMOD '01: Proceedings of the 2001 ACM SIGMOD International Conference on Management of data.
38. Zelle, J. M., Thompson, C. A., Califf, M. E., & Mooney, R. J. (1995). Inducing logic programs without explicit negative examples. In Proceedings of the Fifth International Workshop on Inductive Logic Programming.