Advertisement

JUDIE

  • Eli CortezEmail author
  • Altigran S. da Silva
Chapter
  • 973 Downloads
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

This chapter presents Joint Unsupervised Structure Discovery and Information Extraction (JUDIE) a method for addressing the IETS problem. JUDIE was presented in (Cortez et al. 2011). First, it is introduced the scenario to which JUDIE is targeted to, then we go over the proposed solution detailing all the steps that comprise JUDIE. Finally, an experimental evaluation of JUDIE is presented, comparing its result with different baselines available in the literature.

Keywords

Information extraction Unsupervised approach Text segmentation Structure discovery Knowledge bases Databases 

References

  1. Agichtein, E., & Ganti, V. (2004). Mining reference tables for automatic text segmentation. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 20–29). USA: Seattle.Google Scholar
  2. Barbosa, L., & Freire, J. (2010). Using Latent-structure to Detect Objects on the Web. Proceedings of the Workshop on Web and Databases (pp. 1–6). USA: Indianapolis.Google Scholar
  3. Borkar, V., Deshmukh, K., & Sarawagi, S. (2001). Automatic Segmentation of Text into Structured Records. Proceedings of the ACM SIGMOD International Conference on Management of Data Conference (pp. 175–186). USA: Santa Barbara.Google Scholar
  4. Buttler, D., Liu, L., & Pu, C. (2001). A fully automated object extraction system for the World Wide Web. Proceedings of the International Conference on Distributed Computing Systems (pp. 361–370). USA: Washington.Google Scholar
  5. Cohen, W. W., & Sarawagi, S. (2004). Exploiting dictionaries in named entity extraction: combining semi-markov extraction processes and data integration methods. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 89–98). USA: Seattle.Google Scholar
  6. Cortez, E., da Silva, A., Gonçalves, M., & de Moura, E. (2010). ONDUX: On-Demand Unsupervised Learning for Information Extraction. Proceedings of the ACM SIGMOD International Conference on Management of Data Conference (pp. 807–818). USA: Indianapolis.Google Scholar
  7. Cortez, E., da Silva, A. S., de Moura, E. S., & Laender, A. H. F. (2011). Joint unsupervised structure discovery and information extraction. Proceedings of the ACM SIGMOD International Conference on Management of Data Conference (pp. 541–552). Athens: Greece.Google Scholar
  8. de Oliveira, D. P., & da Silva, A. S. (2006). Extrao de dados de pginas web ricas em dados na ausłncia de informaes estruturais. Master’s thesis: Universidade Federal do Amazonas.Google Scholar
  9. Embley, D., Campbell, D., Jiang, Y., Liddle, S., Lonsdale, D., Ng, Y., et al. (1999). Conceptual-model-based data extraction from multiple-record web pages. Data and Knowledge Engineering, 31(3), 227–251.Google Scholar
  10. Lafferty, J., McCallum, A., & Pereira, F. (2001). Conditional random fields: Probabilistic models for segmenting and labeling sequence data. Proceedings of the ICML International Conference on Machine Learning (pp. 282–289). USA: Williamstown.Google Scholar
  11. Mansuri, I. R., & Sarawagi, S. (2006). Integrating unstructured data into relational databases. Proceedings of the IEEE ICDE International Conference on Data Engineering (pp. 29–41). USA: Atlanta.Google Scholar
  12. Pearl, J., & Shafer, G. (1988). Probabilistic reasoning in intelligent systems: Networks of plausible inference. Morgan Kaufmann.Google Scholar
  13. Shannon, C. E. (2001). A mathematical theory of communication. ACM SIGMOBILE Mobile Computing and Communications Review, 5(1), 3–55.Google Scholar
  14. Zhao, C., Mahmud, J., & Ramakrishnan, I. (2008). Exploiting structured reference data for unsupervised text segmentation with conditional random fields. Proceedings of the SIAM International Conference on Data Mining (pp. 420–431). USA: Atlanta.Google Scholar

Copyright information

© The Author(s) 2013

Authors and Affiliations

  1. 1.Instituto de ComputaçãoUniversidade Federal do AmazonasManausBrazil

Personalised recommendations