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].
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Arasu, A., Chaudhuri, S., Kaushik, R.: Learning string transformations from examples. PVLDBÂ 2(1) (2009)
Beskales, G., Ilyas, I.F., Golab, L.: Sampling the repairs of functional dependency violations under hard constraints. In: VLDB 2010 (2010)
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)
Deutch, D., Greenshpan, O., Kostenko, B., Milo, T.: Using markov chain monte carlo to play trivia. In: ICDE, pp. 1308–1311 (2011)
Deutch, D., Koch, C., Milo, T.: On probabilistic fixpoint and Markov chain query languages. In: PODS, pp. 215–226 (2010)
Dekel, O., Shamir, O.: Vox populi: Collecting high-quality labels from a crowd. In: COLT (2009)
Franklin, M.J., Kossmann, D., Kraska, T., Ramesh, S., Xin, R.: Crowddb: answering queries with crowdsourcing. In: SIGMOD (2011)
Galland, A., Abiteboul, S., Marian, A., Senellart, P.: Corroborating information from disagreeing views. In: WSDM 2010 (2010)
Howe, J.: The rise of crowdsourcing. Wired Magazine - Issue 14.06 (June 2006)
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)
Ma, H., Chandrasekar, R., Quirk, C., Gupta, A.: Improving search engines using human computation games. In: CIKM 2009 (2009)
Parameswaran, A.G., Polyzotis, N.: Answering queries using humans, algorithms and databases. In: CIDR, pp. 160–166 (2011)
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)
Su, Q., Pavlov, D., Chow, J.-H., Baker, W.C.: Internet-scale collection of human-reviewed data. In: WWW 2007 (2007)
Robert, C.P., Casella, G.: Monte Carlo Statistical Methods. Springer Texts in Statistics. Springer, Heidelberg (2005)
von Ahn, L., Dabbish, L.: Designing games with a purpose. Commun. ACM 51(8), 58–67 (2008)
Free GPS Navigation with Turn by Turn - Waze, http://www.waze.com/
The Internet Movie Database (IMDb), http://www.imdb.com/
Tripadvisor, http://www.tripadvisor.com/
Wikiepdia, http://www.wikipedia.org/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Milo, T. (2011). Crowd-Based Data Sourcing. In: Kikuchi, S., Madaan, A., Sachdeva, S., Bhalla, S. (eds) Databases in Networked Information Systems. DNIS 2011. Lecture Notes in Computer Science, vol 7108. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25731-5_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-25731-5_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25730-8
Online ISBN: 978-3-642-25731-5
eBook Packages: Computer ScienceComputer Science (R0)