Advertisement

Abstract

Harnessing a crowd of Web users for the collection of mass data has recently become a wide-spread phenomenon [9]. Wikipedia [20] is probably the earliest and best known example of crowd-sourced data and an illustration of what can be achieved with a crowd-based data sourcing model. Other examples include social tagging systems for images, which harness millions of Web users to build searchable databases of tagged images; traffic information aggregators like Waze [17]; and hotel and movie ratings like TripAdvisor [19] and IMDb [18].

Keywords

Database Instance Movie Rating Internet Movie Database Database Repair Style Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Arasu, A., Chaudhuri, S., Kaushik, R.: Learning string transformations from examples. PVLDB 2(1) (2009)Google Scholar
  2. 2.
    Beskales, G., Ilyas, I.F., Golab, L.: Sampling the repairs of functional dependency violations under hard constraints. In: VLDB 2010 (2010)Google Scholar
  3. 3.
    Boim, R., Greenshpan, O., Milo, T., Novgorodov, S., Polyzotis, N., Tan, W.: Asking the Right Questions in Crowd Data Sourcing. To appear in ICDE (2012)Google Scholar
  4. 4.
    Deutch, D., Greenshpan, O., Kostenko, B., Milo, T.: Using markov chain monte carlo to play trivia. In: ICDE, pp. 1308–1311 (2011)Google Scholar
  5. 5.
    Deutch, D., Koch, C., Milo, T.: On probabilistic fixpoint and Markov chain query languages. In: PODS, pp. 215–226 (2010)Google Scholar
  6. 6.
    Dekel, O., Shamir, O.: Vox populi: Collecting high-quality labels from a crowd. In: COLT (2009)Google Scholar
  7. 7.
    Franklin, M.J., Kossmann, D., Kraska, T., Ramesh, S., Xin, R.: Crowddb: answering queries with crowdsourcing. In: SIGMOD (2011)Google Scholar
  8. 8.
    Galland, A., Abiteboul, S., Marian, A., Senellart, P.: Corroborating information from disagreeing views. In: WSDM 2010 (2010)Google Scholar
  9. 9.
    Howe, J.: The rise of crowdsourcing. Wired Magazine - Issue 14.06 (June 2006)Google Scholar
  10. 10.
    Jampani, R., Xu, F., Wu, M., Perez, L.L., Jermaine, C., Haas, P.J.: Mcdb: a monte carlo approach to managing uncertain data. In: SIGMOD 2008 (2008)Google Scholar
  11. 11.
    Ma, H., Chandrasekar, R., Quirk, C., Gupta, A.: Improving search engines using human computation games. In: CIKM 2009 (2009)Google Scholar
  12. 12.
    Parameswaran, A.G., Polyzotis, N.: Answering queries using humans, algorithms and databases. In: CIDR, pp. 160–166 (2011)Google Scholar
  13. 13.
    Parameswaran, A.G., Das Sarma, A., Garcia-Molina, H., Polyzotis, N., Widom, J.: Human-assisted graph search: it’s okay to ask questions. PVLDB 4(5), 267–278 (2011)Google Scholar
  14. 14.
    Su, Q., Pavlov, D., Chow, J.-H., Baker, W.C.: Internet-scale collection of human-reviewed data. In: WWW 2007 (2007)Google Scholar
  15. 15.
    Robert, C.P., Casella, G.: Monte Carlo Statistical Methods. Springer Texts in Statistics. Springer, Heidelberg (2005)Google Scholar
  16. 16.
    von Ahn, L., Dabbish, L.: Designing games with a purpose. Commun. ACM 51(8), 58–67 (2008)Google Scholar
  17. 17.
    Free GPS Navigation with Turn by Turn - Waze, http://www.waze.com/
  18. 18.
    The Internet Movie Database (IMDb), http://www.imdb.com/
  19. 19.
  20. 20.

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Tova Milo
    • 1
  1. 1.School of Computer ScienceTel Aviv UniversityTel AvivIsrael

Personalised recommendations