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dc.contributor.authorFeng, Amber
dc.contributor.authorFranklin, Michael J.
dc.contributor.authorKossmann, Donald
dc.contributor.authorKraska, Tim
dc.contributor.authorMadden, Samuel R.
dc.contributor.authorRamesh, Sukriti
dc.contributor.authorWang, Andrew
dc.contributor.authorXin, Reynold
dc.date.accessioned2014-09-26T12:16:19Z
dc.date.available2014-09-26T12:16:19Z
dc.date.issued2011-08
dc.identifier.issn2150-8097
dc.identifier.urihttp://hdl.handle.net/1721.1/90378
dc.description.abstractDatabases often give incorrect answers when data are missing or semantic understanding of the data is required. Processing such queries requires human input for providing the missing information, for performing computationally difficult functions, and for matching, ranking, or aggregating results based on fuzzy criteria. In this demo we present CrowdDB, a hybrid database system that automatically uses crowdsourcing to integrate human input for processing queries that a normal database system cannot answer. CrowdDB uses SQL both as a language to ask complex queries and as a way to model data stored electronically and provided by human input. Furthermore, queries are automatically compiled and optimized. Special operators provide user interfaces in order to integrate and cleanse human input. Currently CrowdDB supports two crowdsourcing platforms: Amazon Mechanical Turk and our own mobile phone platform. During the demo, the mobile platform will allow the VLDB crowd to participate as workers and help answer otherwise impossible queries.en_US
dc.language.isoen_US
dc.publisherVLDB Endowmenten_US
dc.relation.isversionofhttp://www.vldb.org/pvldb/vol4.htmlen_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceOther univ. web domainen_US
dc.titleCrowdDB: Query processing with the VLDB crowden_US
dc.typeArticleen_US
dc.identifier.citationFeng, Amber, et al. "CrowdDB: Query processing with the VLDB crowd." Proceedings of the VLDB Endowment, Vol. 4, No. 12 (2011).en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorMadden, Samuel R.en_US
dc.relation.journalProceedings of the VLDB Endowmenten_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsFeng, Amber; Franklin, Michael; Kossmann, Donald; Kraska, Tim; Madden, Samuel R.; Ramesh, Sukriti; Wang, Andrew; Xin, Reynolden_US
dc.identifier.orcidhttps://orcid.org/0000-0002-7470-3265
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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