A framework for learning Web wrappers from the crowd

WWW 2013 - Proceedings of the 22nd International Conference on World Wide Web

Volumn , Issue , 2013, Pages 261-271

  Crescenzi, Valter ^a   Merialdo, Paolo ^a   Qiu, Disheng ^a  

^a ROMA TRE UNIVERSITY   (Italy)

Author keywords

Active learning; Crowdsourcing; Wrapper generation

Indexed keywords

CROWDSOURCING; WEBSITES;

ACTIVE LEARNING; INFERENCE ALGORITHM; INFERENCE SYSTEMS; MANUAL ANNOTATION; MEMBERSHIP QUERY; MINIMIZING THE NUMBER OF; TRAINING SETS; WRAPPER GENERATION;

INFERENCE ENGINES;

EID: 84893059618     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2488388.2488412     Document Type: Conference Paper

References (16)

1. D. Angluin. Queries revisited. Theor. Comput. Sci., 313(2):175-194, 2004.
2. A. Arasu and H. Garcia-Molina. Extracting structured data from web pages. In SIGMOD Conference, pages 337-348. ACM, 2003.
3. M.-F. Balcan, S. Hanneke, and J. W. Vaughan. The true sample complexity of active learning. Machine Learning, 80(2-3):111-139, 2010.
4. C.-H. Chang and S.-C. Lui. IEPAD: information extraction based on pattern discovery. In WWW, pages 681-688, 2001.
5. R. Creo, V. Crescenzi, D. Qiu, and P. Merialdo. Minimizing the costs of the training data for learning web wrappers. In VLDS, pages 35-40, 2012.
6. V. Crescenzi and G. Mecca. Automatic information extraction from large websites. J. ACM, 51(5):731-779, 2004.
7. V. Crescenzi and P. Merialdo. Wrapper inference for ambiguous web pages. Applied Artificial Intelligence, 22(1&2):21-52, 2008.
8. N. N. Dalvi, R. Kumar, and M. A. Soliman. Automatic wrappers for large scale web extraction. PVLDB, 4(4):219-230, 2011.
9. U. Irmak and T. Suel. Interactive wrapper generation with minimal user effort. In WWW, pages 553-563. ACM, 2006.
10. T. Furche, G. Gottlob, G. Grasso, O. Gunes, X. Guo, A. Kravchenko, G. Orsi, C. Schallhart, A. J. Sellers, and C. Wang. DIADEM: domain-centric, intelligent, automated data extraction methodology. In WWW (Companion Volume), pages 267-270. ACM, 2012.
11. G. Gottlob, C. Koch, R. Baumgartner, M. Herzog, and S. Flesca. The lixto data extraction project - back and forth between theory and practice. In PODS, pages 1-12. ACM, 2004.
12. I. Muslea, S. Minton, and C. A. Knoblock. Active learning with multiple views. J. Artif. Intell. Res. (JAIR), 27:203-233, 2006.
13. B. Settles. Active learning literature survey. Computer Sciences Technical Report 1648, University of Wisconsin-Madison, 2009.
14. J. Shawe-Taylor, P. L. Bartlett, R. C. Williamson, and M. Anthony. Structural risk minimization over data-dependent hierarchies. IEEE Transactions on Information Theory, 44(5):1926-1940, 1998.
15. V. Vapnik. An overview of statistical learning theory. IEEE Transactions on Neural Networks, 10(5):988-999, 1999.
16. Y. Zhai and B. Liu. Structured data extraction from the web based on partial tree alignment. IEEE Trans. Knowl. Data Eng., 18(12):1614-1628, 2006.