Crowdsourced Databases: Query Processing with People

By Adam Marcus, Eugene Wu, Samuel Madden, Rob Miller. 2011

244 citations recorded by the source corpus.

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Citations in the corpus

A Survey on Data Collection for Machine Learning: A Big Data - AI Integration Perspective (2018, methodology): “Data generation Crowdsourcing Gathering [45], [46], [47], [48], [49], [50], [51], [52], [53], [54] Processing [49], [50], [55], [56]”
Human-powered Sorts and Joins (2011, methodology): “An initial version of this design appeared in a short paper [11], though the design has since been reﬁned.”
CrowdER: Crowdsourcing Entity Resolution (2012, background): “Entity resolution is easily expressed as a query in a crowd-enabled query processing system such as CrowdDB [13] or Qurk [20].”
Truth Inference in Crowdsourcing: Is the Problem Solved? (2017, background): “A naive solution is Majority Voting (MV) [20, 39, 37], which regards the choice answered by majority workers as the truth.”
Foundations of Crowd Data Sourcing (2015, methodology): “, [10, 16, 20, 21]) suggests the construction of declarative frameworks, which outsource the harvesting of certain missing values or missing tuples to the crowd.”
Counting with the Crowd (2012, background): “In the databases ﬁeld, several crowd-powered databases and query executors including CrowdDB [10], Deco [19], Jabberwocky [1], and our own Qurk [16] enable users to issue data-oriented tasks to crowd workers.”
GeoCrowd: enabling query answering with spatial crowdsourcing (2012, methodology): “Moreover, the database community has utilized crowdsourcing in relational query processing [19, 25, 27].”
Crowdsourced enumeration queries (2013, background): “These include CrowdDB [2], Qurk [3], and sCOOP [4].”
Corleone: hands-off crowdsourcing for entity matching (2014, background): “In the database community, the work [9, 23, 20] build crowdsourced RDBMSs.”
Crowdsourced Data Management: A Survey (2016, methodology): “Qurk [80] uses a SQL-based query language with user-”
Challenges in Data Crowdsourcing (2016, methodology): “Systems of this type include Deco [40], CrowdDB [21], and Qurk [33].”
CrowdScreen: algorithms for filtering data with humans (2012, background): “Recently, there has been a lot of interest in the database research community in using crowdsourcing within a database [2, 3, 4, 12, 17].”
CrowdDB: answering queries with crowdsourcing (2011, methodology): “Two papers on the topic appeared in the recent CIDR 2011 conference [20, 23].”
CDAS: A Crowdsourcing Data Analytics System (2012, background): “Qurk [16][15] and CrowdDB [6] are two examples of databases with crowdsourcing support.”
Crowdsourced Data Management: Industry and Academic Perspectives (2015, methodology): “In Chapter 4, we described several tools for declarative and imperative specification of crowd work, with the aim of reducing developer load, and seamless optimization [126, 144, 80, 116, 133, 22] for common crowdsourcing operations.”
Platemate: crowdsourcing nutritional analysis from food photographs (2011, methodology): “For example, TurKit [9] lets requesters program crowds in JavaScript, Qurk [14] integrated crowds into SQL, and CrowdForge [8] parallelized work with MapReduce scripts.”
Evaluation on crowdsourcing research: Current status and future direction (2012, background): “…to support, mediate, and facilitate their work on user studies (Alonso et al. 2008; Eckert et al. 2010; Franklin et al. 2011; Kittur et al. 2008; Marcus et al. 2011), cataloging (Holley 2009), and transportation plan (Brabham 2009), The above examination leads us to conclude that crowd-sourcing…”