Abstract
Many popular sites, such as Wikipedia and Tripadvisor, rely on public participation to gather information - a process known as crowd data sourcing. While this kind of collective intelligence is extremely valuable, it is also fallible, and policing such sites for inaccuracies or missing material is a costly undertaking. In this talk we will overview the MoDaS project that investigates how database technology can be put to work to effectively gather information from the public, efficiently moderate the process, and identify questionable input with minimal human interaction [1-4, 7]. We will consider the logical, algorithmic, and methodological foundations for the management of large scale crowd-sourced data as well as the development of applications over such information.
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
Similar content being viewed by others
References
Amsterdamer, Y., Grossman, Y., Milo, T., Senellart, P.: Crowd mining. In: SIGMOD (2013)
Boim, R., Greenshpan, O., Milo, T., Novgorodov, S., Polyzotis, N., Tan, W.-C.: Asking the right questions in crowd data sourcing. In: ICDE, pp. 1261–1264 (2012)
Davidson, S., Khanna, S., Milo, T., Roy, S.: Using the crowd for top-k and group-by queries. In: ICDT (2013)
Deutch, D., Greenshpan, O., Kostenko, B., Milo, T.: Declarative platform for data sourcing games. In: WWW, pp. 779–788 (2012)
Franklin, M.J., Kossmann, D., Kraska, T., Ramesh, S., Xin, R.: Crowddb: answering queries with crowdsourcing. In: SIGMOD (2011)
Guo, S., Parameswaran, A.G., Garcia-Molina, H.: So who won?: dynamic max discovery with the crowd. In: SIGMOD Conference, pp. 385–396 (2012)
Kaplan, H., Lotosh, I., Milo, T., Novgorodov, S.: Answering planning queries with the crowd. In: VLDB (2013)
Liu, X., Lu, M., Ooi, B.C., Shen, Y., Wu, S., Zhang, M.: Cdas: A crowdsourcing data analytics system. PVLDB 5(10), 1040–1051 (2012)
Marcus, A., Wu, E., Madden, S., Miller, R.C.: Crowdsourced databases: Query processing with people. In: CIDR, pp. 211–214 (2011)
Park, H., Pang, R., Parameswaran, A.G., Garcia-Molina, H., Polyzotis, N., Widom, J.: Deco: A system for declarative crowdsourcing. PVLDB 5(12), 1990–1993 (2012)
Selke, J., Lofi, C., Balke, W.-T.: Pushing the boundaries of crowd-enabled databases with query-driven schema expansion. PVLDB 5(6), 538–549 (2012)
Wang, J., Kraska, T., Franklin, M.J., Feng, J.: Crowder: Crowdsourcing entity resolution. PVLDB 5(11), 1483–1494 (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Milo, T. (2013). Making Collective Wisdom Wiser. In: Decker, H., Lhotská, L., Link, S., Basl, J., Tjoa, A.M. (eds) Database and Expert Systems Applications. DEXA 2013. Lecture Notes in Computer Science, vol 8055. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40285-2_3
Download citation
DOI: https://doi.org/10.1007/978-3-642-40285-2_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40284-5
Online ISBN: 978-3-642-40285-2
eBook Packages: Computer ScienceComputer Science (R0)