OpenEval: Web information query evaluation

Proceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013

Volumn , Issue , 2013, Pages 1163-1169

  Samadi, Mehdi ^a   Veloso, Manuela ^a   Blum, Manuel ^a  

^a Carnegie Mellon University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATED AGENTS; F1 SCORES; ON-LINE INFORMATION; POSITIVE EXAMPLES; WEB INFORMATION;

ARTIFICIAL INTELLIGENCE;

EID: 84893411776     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (38)

1. Agichtein, E., and Gravano, L. 2000. Snowball: extracting relations from large plain-text collections. In Proceedings of the fifth ACM conference on Digital libraries, DL '00, 85-94.
2. Auer, P. 2003. Using confidence bounds for exploitationexploration trade-offs. J. Mach. Learn. Res. 3:397-422.
3. Blum, A. L., and Langley, P. 1997. Selection of relevant features and examples in machine learning. Artif. Intell. 97(1-2):245-271.
4. Bollacker, K.; Evans, C.; Paritosh, P.; Sturge, T.; and Taylor, J. 2008. Freebase: a collaboratively created graph database for structuring human knowledge. In SIGMOD '08, 1247-1250.
5. Califf, M. E., and Mooney, R. J. 2003. Bottom-up relational learning of pattern matching rules for information extraction. J. Mach. Learn. Res. 4:177-210.
6. Carlson, A.; Betteridge, J.; Kisiel, B.; Settles, B.; Jr., E. R. H.; and Mitchell, T. M. 2010. Toward an architecture for never-ending language learning. In AAAI.
7. Cimiano, P., and Staab, S. 2004. Learning by googling. SIGKDD Explor. Newsl. 6(2):24-33.
8. Cimiano, P., and Volker, J. 2005. Towards large-scale, opendomain and ontology-based named entity classification. In RANLP, 166-172.
9. Cimiano, P.; Ladwig, G.; and Staab, S. 2005. Gimme? the context: context-driven automatic semantic annotation with c-pankow. In WWW'05, 332-341. New York, NY, USA: ACM.
10. Ciravegna, F. 2001. Adaptive information extraction from text by rule induction and generalisation. In IJCAI'01, 1251-1256. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.
11. Clemen, R. T. 1989. Combining forecasts: A review and annotated bibliography. International Journal of Forecasting 5(4):559-583.
12. Dietterich, T. G. 1998. Machine-learning research: Four current directions. The AI Magazine 18(4):97-136.
13. Downey, D.; Etzioni, O.; and Soderland, S. 2010. Analysis of a probabilistic model of redundancy in unsupervised information extraction. Artif. Intell. 174(11):726-748.
14. Etzioni, O.; Cafarella, M.; Downey, D.; Kok, S.; Popescu, A.-M.; Shaked, T.; Soderland, S.; Weld, D. S.; and Yates, A. 2004. Webscale information extraction in knowitall: (preliminary results). In WWW '04, 100-110. New York, NY, USA: ACM.
15. Etzioni, O.; Banko, M.; Soderland, S.; andWeld, D. S. 2008. Open information extraction from the web. Commun. ACM 51(12):68-74.
16. Etzioni, O.; Fader, A.; Christensen, J.; Soderland, S.; and Mausam. 2011. Open information extraction: The second generation. In Walsh, T., ed., IJCAI, 3-10. IJCAI/AAAI.
17. Fader, A.; Soderland, S.; and Etzioni, O. 2011. Identifying relations for open information extraction. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP '11, 1535-1545. Stroudsburg, PA, USA: Association for Computational Linguistics.
18. Fang, Y., and Chang, K. C.-C. 2011. Searching patterns for relation extraction over the web: rediscovering the pattern-relation duality. In WSDM '11, 825-834. New York, NY, USA: ACM.
19. Freedman, M.; Loper, E.; Boschee, E.; and Weischedel, R. 2010. Empirical studies in learning to read. In Proceedings of the NAACL HLT 2010, FAM-LbR '10, 61-69.
20. Gittins, J. C., and Jones, D. M. 1974. A Dynamic Allocation Index for the Sequential Design of Experiments. In Gani, J., ed., Progress in Statistics. Amsterdam, NL: North-Holland. 241-266.
21. Hoffmann, R.; Zhang, C.; and Weld, D. S. 2010. Learning 5000 relational extractors. In ACL '10, 286-295. Stroudsburg, PA, USA: Association for Computational Linguistics.
22. Kollar, T.; Samadi, M.; and Veloso, M. 2012. Enabling robots to find and fetch objects by querying the web. In AAMAS '12, 1217-1218.
23. Magnini, B.; Negri, M.; Prevete, R.; and Tanev, H. 2002. Is it the right answer? exploiting web redundancy for answer validation. In ACL-40, 425-432.
24. Mausam; Schmitz, M.; Soderland, S.; Bart, R.; and Etzioni, O. 2012. Open language learning for information extraction. In EMNLP-CoNLL, 523-534. ACL.
25. McDowell, L. K., and Cafarella, M. 2006. Ontology-driven information extraction with ontosyphon. In ISWC'06, 428-444. Berlin, Heidelberg: Springer-Verlag.
26. Mintz, M.; Bills, S.; Snow, R.; and Jurafsky, D. 2009. Distant supervision for relation extraction without labeled data. In ACL '09, 1003-1011.
27. Mladenić, D.; Brank, J.; Grobelnik, M.; and Milic-Frayling, N. 2004. Feature selection using linear classifier weights: interaction with classification models. In Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR '04, 234-241. New York, NY, USA: ACM.
28. Nakov, P., and Hearst, M. 2005. Search engine statistics beyond the n-gram: application to noun compound bracketing. In CONLL '05, 17-24. Stroudsburg, PA, USA: Association for Computational Linguistics.
29. Pantel, P., and Pennacchiotti, M. 2006. Espresso: leveraging generic patterns for automatically harvesting semantic relations. In ACL-44, 113-120.
30. Poon, H.; Christensen, J.; Domingos, P.; Etzioni, O.; Hoffmann, R.; Kiddon, C.; Lin, T.; Ling, X.; Mausam; Ritter, A.; Schoenmackers, S.; Soderland, S.; Weld, D.; Wu, F.; and Zhang, C. 2010. Machine reading at the university of washington. In Proceedings of the NAACL HLT 2010, FAM-LbR '10, 87-95.
31. Samadi, M.; Kollar, T.; and Veloso, M. M. 2012. Using the web to interactively learn to find objects. In Hoffmann, J., and Selman, B., eds., AAAI. AAAI Press.
32. Sekine, S. 2006. On-demand information extraction. In COLINGACL '06, 731-738.
33. Shinyama, Y., and Sekine, S. 2006. Preemptive information extraction using unrestricted relation discovery. In HLT-NAACL '06, 304-311.
34. Soderl, S.; Etzioni, O.; Shaked, T.; andWeld, D. S. July 2004. The use of web-based statistics to validate information extraction. In AAAI Workshop on Adaptive Text Extraction and Mining.
35. Sutton, R. S. 1990. Integrated architectures for learning, planning, and reacting based on approximating dynamic programming. In ICML, 216-224. Morgan Kaufmann.
36. Turney, P. 2001. Mining the web for synonyms: Pmi-ir versus lsa on toefl.
37. Uyar, A. 2009. Investigation of the accuracy of search engine hit counts. J. Inf. Sci. 35:469-480.
38. Zhang, Z. 2004. Weakly-supervised relation classification for information extraction. In Proceedings of the thirteenth ACM international conference on Information and knowledge management, CIKM '04, 581-588. New York, NY, USA: ACM.