Automatically utilizing secondary sources to align information across sources

AI Magazine

Volumn 26, Issue 1, 2005, Pages 33-44

  Michalowski, Martin ^a   Thakkar, Snehal ^a   Knoblock, Craig A ^b  

^a University of Southern California ^*  (United States)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA STRUCTURES; SEMANTICS; TELECOMMUNICATION SERVICES; TEXT PROCESSING; WORLD WIDE WEB; XML;

DATA SOURCES; INFORMATION INTEGRATION; RECORD LINKAGE SYSTEMS; SEMANTIC WEB; TEXT FORMAT; WEB SERVICES;

DATA RECORDING;

EID: 17244376008     PISSN: 07384602     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (26)

1. Abe, N.; and Mamitsuka, H. 1998. Query Learning Strategies using Boosting and Bagging. In Proceedings of the Fifteenth International Conference on Machine Learning. San Francisco: Morgan Kaufmann Publishers.
2. Bayardo Jr., R. J.; Bohrer, W.; Brice, R.; Cichocki, A.; Flower, J.; Helal, A.; Kashyap, V.; Ksiezyk, T.; Martin, G.; Nodine, M.; Rashid, M.; Rusinkiewicz, M;. Shea, R.; Unnikrishnan, C.; Unruh, A.; and Woelk, D. 1997. Infosleuth: Agent-based Semantic Integration of Information in Open and Dynamic Environments. In Proceedings of the ACM SIGMOD International Conference on Management of Data. New York: Association for Computing Machinery.
3. Bilenko, M.; and Mooney, R. J. 2003. Adaptive Duplicate Detection Using Learnable String Similarity Measures. In Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: Association for Computing Machinery.
4. Breiman, L. 1996. Bagging Predictors. Machine Learning 24(2): 123-140.
5. Chaudhuri, S.; Ganjam, K.; Ganti, V.; and Motwani, R. 2003. Robust and Efficient Fuzzy Match for Online Data Cleaning. In Proceedings of the ACM SIGMOD International Conference on Management of Data. New York: Association for Computing Machinery.
6. Dhamankar, R.; Lee, Y.; Doan, A.; Halevy, A.; and Domingos, R 2004. iMAP: Discovering Complex Semantic Mappings between Database Schemas. In Proceedings of the ACM SIGMOD International Conference on Management of Data. New York: Association for Computing Machinery.
7. Doan, A.; Lu, Y.; Lee, Y;. and Han, J. 2003. Object Matching for Data Integration: A Profile-Based Approach. IEEE Intelligent Systems 18(5): 54-59.
8. Garcia-Molina, H.; Hammer, J.; Ireland, K.; Papakonstantinou, Y.; Ullman, J.; and Widom, J. 1995. Integrating and Accessing Heterogeneous Information Sources in TSIMMIS. In Information Gathering from Heterogeneous, Distributed Environments: Papers from the AAAI Spring Symposium. Technical Report SS-95-08. Menlo Park, CA: American Association for Artificial Intelligence.
9. Genesereth, M. R.; Keller, A. M.; and Duschka, O. M. 1997. InfoMaster: An Information Integration System. In Proceedings of the ACM SIGMOD International Conference on Management of Data. New York: Association for Computing Machinery.
10. Hernández, M. A.; and Stolfo, S. J. 1995. The Merge/Purge Problem for Large Databases. In Proceedings of the ACM SIGMOD International Conference on Management of Data. New York: Association for Computing Machinery.
11. Hsu, C.-N.; and Dung, M.-T. 1998. Generating Finite-State Transducers for Semistructured Data Extraction from the Web. Information Systems Journal 23(8): 521-538.
12. Jin, L.; Li, C.; and Mehrotra, S. 2003. Efficient Record Linkage in Large Data Sets. In Proceedings of the Eighth International Conference on Database Systems for Advanced Applications (DASFAA 2003). Piscataway, NJ: Institute of Electrical and Electronics Engineers.
13. Knoblock, C., S.; Minton, J. L.; Ambite, N.; Ashish, N.; Muslea, I.; Philpot, A.; and Tejada, S. 2001. The ARIADNE Approach to Web-Based Information Integration. International Journal on Intelligent Cooperative Information Systems 10(1-2): 145-169.
14. Levy, A. Y.; Rajaraman, A.; and Ordille, J. J. 1996a. Query-Answering Algorithms for Information Agents. In Proceedings of the Thirteenth National Conference on Artificial Intelligence. Menlo Park, CA: AAAI Press.
15. Levy, A. Y.; Rajaraman, A.; and Ordille, J. J. 1996b. Querying Heterogeneous Information Sources Using Source Descriptions. In Proceedings of the Twenty-Second International Conference on Very Large Databases. San Francisco: Morgan Kaufmann Publishers.
16. Madhavan, J.; and Halevy, A. 2003. Composing Mappings among Data Sources. In Proceedings of the Twenty-Ninth International Conference on Very Large Databases. San Francisco: Morgan Kaufmann Publishers.
17. Michalowski, M.; Thakkar, S.; and Knoblock, C. A. 2003. Exploiting Secondary Sources for Automatic Object Consolidation. Paper presented at the First KDD Workshop on Data Cleaning, Record Linkage, and Object Consolidation, Washington, D.C., 27 August.
18. Miller, R. J.; Haas, L. M.; and Hernández, M. A. 2000. Schema Mapping as Query Discovery. In Proceedings of the Twenty-Sixth International Conference on Very Large Data Bases. San Francisco: Morgan Kaufmann Publishers.
19. Monge, A. E.; and Elkan, C. 1996. The Field Matching Problem: Algorithms and Applications. In Proceedings of the Second InternationalConference on Knowledge Discovery and Data Mining. Menlo Park, CA: AAAI Press.
20. Muslea, I.; Minton, S.; and Knoblock, C. A. 2001. Hierarchical Wrapper Induction for Semistructured Information Sources. Autonomous Agents and Multi-Agent Systems 4(1): 93-114.
21. Quinlan, J. R. 1996. Improved Use of Continuous Attributes in C4.5. Journal of Artficial Intelligence Research. 4: 77-90.
22. Raman, V.; and Hellerstein, J. M. 2001. Potter's Wheel: An Interactive Data Cleaning System. In Proceedings of the Twenty-Seventh International Conference on Very Large Data Bases, 381-390. San Francisco: Morgan Kaufmann Publishers.
23. Sarawagi, S.; and Bhamidipaty, A. 2002. Interactive Deduplication Using Active Learning. In Proceedings of the Eighth ACM SIGKDD Conference on Knowledge Discovery and Data Minning. New York: Association for Computing Machinery.
24. Tejada, S.; Knoblock, C. A.; and Minton, S. 2001. Learning Object Identification Rules for Information Integration. Information Systems 26(8): 607-633.
25. Tejada, S.; Knoblock, C. A.; and Minton, S. 2002. Learning Domain-Independent String Transformation Weights for High Accuracy Object Identification. In Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: Association for Computing Machinery.
26. Thakkar, S.; Ambite, J. L.; and Knoblock, C. A. 2003. A View Integration Approach to Dynamic Composition of Web Services. Paper presented at the 2003 ICAPS Workshop on Planning for Web Services, Trento, Italy, 10 June.