Abstract
It is rather inconvenient to interact with crowdsourcing platforms, as the platforms require one to set various parameters and even write code. Thus, inspired by traditional DBMS, crowdsourcing database systems have been designed and built.
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
References
Amazon mechanical turk. https://www.mturk.com/
Crowdflower. http://www.crowdflower.com
Davidson, S.B., Khanna, S., Milo, T., Roy, S.: Using the crowd for top-k and group-by queries. In: ICDT, pp. 225–236 (2013)
Fan, J., Zhang, M., Kok, S., Lu, M., Ooi, B.C.: Crowdop: Query optimization for declarative crowdsourcing systems. IEEE Trans. Knowl. Data Eng. 27(8), 2078–2092 (2015)
Feng, A., Franklin, M.J., Kossmann, D., Kraska, T., Madden, S., Ramesh, S., Wang, A., Xin, R.: Crowddb: Query processing with the vldb crowd. PVLDB 4(12), 1387–1390 (2011)
Franklin, M.J., Kossmann, D., Kraska, T., Ramesh, S., Xin, R.: Crowddb: answering queries with crowdsourcing. In: SIGMOD, pp. 61–72 (2011)
Guo, S., Parameswaran, A.G., Garcia-Molina, H.: So who won?: dynamic max discovery with the crowd. In: SIGMOD, pp. 385–396 (2012)
Li, G., Chai, C., Fan, J., Weng, X., Li, J., Zheng, Y., Li, Y., Yu, X., Zhang, X., Yuan, H.: CDB: optimizing queries with crowd-based selections and joins. In: SIGMOD, pp. 1463–1478 (2017)
Marcus, A., Karger, D.R., Madden, S., Miller, R., Oh, S.: Counting with the crowd. PVLDB 6(2), 109–120 (2012)
Marcus, A., Wu, E., Karger, D.R., Madden, S., Miller, R.C.: Human-powered sorts and joins. PVLDB 5(1), 13–24 (2011)
Marcus, A., Wu, E., Madden, S., Miller, R.C.: Crowdsourced databases: Query processing with people. In: CIDR, pp. 211–214 (2011)
Parameswaran, A.G., Garcia-Molina, H., Park, H., Polyzotis, N., Ramesh, A., Widom, J.: Crowdscreen: algorithms for filtering data with humans. In: SIGMOD, pp. 361–372 (2012)
Parameswaran, A.G., Park, H., Garcia-Molina, H., Polyzotis, N., Widom, J.: Deco: declarative crowdsourcing. In: CIKM, pp. 1203–1212. ACM (2012)
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)
Park, H., Widom, J.: Query optimization over crowdsourced data. PVLDB 6(10), 781–792 (2013)
Park, H., Widom, J.: Crowdfill: collecting structured data from the crowd. In: SIGMOD, pp. 577–588 (2014)
Sarma, A.D., Parameswaran, A.G., Garcia-Molina, H., Halevy, A.Y.: Crowd-powered find algorithms. In: ICDE, pp. 964–975 (2014)
Trushkowsky, B., Kraska, T., Franklin, M.J., Sarkar, P.: Crowdsourced enumeration queries. In: ICDE, pp. 673–684 (2013)
Wang, J., Kraska, T., Franklin, M.J., Feng, J.: CrowdER: crowdsourcing entity resolution. PVLDB 5(11), 1483–1494 (2012)
Wang, J., Li, G., Kraska, T., Franklin, M.J., Feng, J.: Leveraging transitive relations for crowdsourced joins. In: SIGMOD, pp. 229–240 (2013)
Yan, T., Kumar, V., Ganesan, D.: Crowdsearch: exploiting crowds for accurate real-time image search on mobile phones. In: MobiSys, pp. 77–90 (2010)
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Li, G., Wang, J., Zheng, Y., Fan, J., Franklin, M.J. (2018). Crowdsourcing Database Systems and Optimization. In: Crowdsourced Data Management. Springer, Singapore. https://doi.org/10.1007/978-981-10-7847-7_6
Download citation
DOI: https://doi.org/10.1007/978-981-10-7847-7_6
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-7846-0
Online ISBN: 978-981-10-7847-7
eBook Packages: Computer ScienceComputer Science (R0)