-
1
-
-
85020469390
-
-
https://docs.aws.amazon.com/AWSMechTurk/latest/RequesterUI/amt-ui.pdf.
-
-
-
-
2
-
-
85020425035
-
-
Amazon mechanical turk. https://www.mturk.com/.
-
-
-
-
3
-
-
85020448368
-
-
Chi-squared. https://en.wikipedia.org/wiki/Chi-squared_distribution.
-
-
-
-
4
-
-
85020429296
-
-
Adult Datset. https://github.com/ipeirotis/Get-Another-Label/tree/master/data.
-
-
-
-
5
-
-
84908213945
-
Crowdsourcing for multiple-choice question answering
-
B. I. Aydin, Y. S. Yilmaz, Y. Li, Q. Li, J. Gao, and M. Demirbas. Crowdsourcing for multiple-choice question answering. In AAAI, pages 2946-2953, 2014.
-
(2014)
AAAI
, pp. 2946-2953
-
-
Aydin, B.I.1
Yilmaz, Y.S.2
Li, Y.3
Li, Q.4
Gao, J.5
Demirbas, M.6
-
6
-
-
0141607824
-
Latent dirichlet allocation
-
D. M. Blei, A. Y. Ng, and M. I. Jordan. Latent dirichlet allocation. JMLR, 3(Jan):993-1022, 2003.
-
(2003)
JMLR
, vol.3
, Issue.JAN
, pp. 993-1022
-
-
Blei, D.M.1
Ng, A.Y.2
Jordan, M.I.3
-
7
-
-
84864239684
-
Asking the right questions in crowd data sourcing
-
R. Boim, O. Greenshpan, T. Milo, S. Novgorodov, N. Polyzotis, and W.-C. Tan. Asking the right questions in crowd data sourcing. In ICDE, pages 1261-1264, 2012.
-
(2012)
ICDE
, pp. 1261-1264
-
-
Boim, R.1
Greenshpan, O.2
Milo, T.3
Novgorodov, S.4
Polyzotis, N.5
Tan, W.-C.6
-
8
-
-
77949817550
-
A survey of entity resolution and record linkage methodologies
-
D. G. Brizan and A. U. Tansel. A survey of entity resolution and record linkage methodologies. Communications of the IIMA, 6(3):5, 2015.
-
(2015)
Communications of the IIMA
, vol.6
, Issue.3
, pp. 5
-
-
Brizan, D.G.1
Tansel, A.U.2
-
10
-
-
80053402398
-
Fast, cheap, and creative: Evaluating translation quality using amazon's mechanical turk
-
C. Callison-Burch. Fast, cheap, and creative: evaluating translation quality using amazon's mechanical turk. In EMNLP, pages 286-295, 2009.
-
(2009)
EMNLP
, pp. 286-295
-
-
Callison-Burch, C.1
-
11
-
-
84979681401
-
Cost-effective crowdsourced entity resolution: A partial-order approach
-
C. Chai, G. Li, J. Li, D. Deng, and J. Feng. Cost-effective crowdsourced entity resolution: A partial-order approach. In SIGMOD, pages 969-984, 2016.
-
(2016)
SIGMOD
, pp. 969-984
-
-
Chai, C.1
Li, G.2
Li, J.3
Deng, D.4
Feng, J.5
-
12
-
-
85020474625
-
-
CrowdFlower. http://crowdflower.com/.
-
-
-
-
13
-
-
85020486903
-
-
Crowdsourcing Datasets. http://dbgroup.cs.tsinghua.edu.cn/ligl/crowddata/.
-
-
-
-
14
-
-
84875617425
-
Using the crowd for top-k and group-by queries
-
S. B. Davidson, S. Khanna, T. Milo, and S. Roy. Using the crowd for top-k and group-by queries. In ICDT, pages 225-236, 2013.
-
(2013)
ICDT
, pp. 225-236
-
-
Davidson, S.B.1
Khanna, S.2
Milo, T.3
Roy, S.4
-
15
-
-
0003102944
-
Maximum likelihood estimation of observer error-rates using the em algorithm
-
A. P. Dawid and A. M. Skene. Maximum likelihood estimation of observer error-rates using the em algorithm. Applied statistics, pages 20-28, 1979.
-
(1979)
Applied statistics
, pp. 20-28
-
-
Dawid, A.P.1
Skene, A.M.2
-
16
-
-
84860873929
-
Zencrowd: Leveraging probabilistic reasoning and crowdsourcing techniques for large-scale entity linking
-
G. Demartini, D. E. Difallah, and P. Cudre-Mauroux. Zencrowd: leveraging probabilistic reasoning and crowdsourcing techniques for large-scale entity linking. In WWW, pages 469-478, 2012.
-
(2012)
WWW
, pp. 469-478
-
-
Demartini, G.1
Difallah, D.E.2
Cudre-Mauroux, P.3
-
19
-
-
84957558382
-
Icrowd: An adaptive crowdsourcing framework
-
J. Fan, G. Li, B. C. Ooi, K.-I. Tan, and J. Feng. icrowd: An adaptive crowdsourcing framework. In SIGMOD, pages 1015-1030, 2015.
-
(2015)
SIGMOD
, pp. 1015-1030
-
-
Fan, J.1
Li, G.2
Ooi, B.C.3
Tan, K.-I.4
Feng, J.5
-
20
-
-
79959958767
-
Crowddb: Answering queries with crowdsourcing
-
M. J. Franklin, D. Kossmann, T. Kraska, S. Ramesh, and R. Xin. Crowddb: answering queries with crowdsourcing. In S1GMOD, pages 61-72, 2011.
-
(2011)
S1GMOD
, pp. 61-72
-
-
Franklin, M.J.1
Kossmann, D.2
Kraska, T.3
Ramesh, S.4
Xin, R.5
-
21
-
-
84936873985
-
Finish them!: Pricing algorithms for human computation
-
Y. Gao and A. Parameswaran. Finish them!: Pricing algorithms for human computation. PVLDB, 7(14):1965-1976, 2014.
-
(2014)
PVLDB
, vol.7
, Issue.14
, pp. 1965-1976
-
-
Gao, Y.1
Parameswaran, A.2
-
22
-
-
84862686874
-
So who won?: Dynamic max discovery with the crowd
-
S. Guo, A. G. Parameswaran, and H. Garcia-Molina. So who won?: dynamic max discovery with the crowd. In SIGMOD, pages 385-396, 2012.
-
(2012)
SIGMOD
, pp. 385-396
-
-
Guo, S.1
Parameswaran, A.G.2
Garcia-Molina, H.3
-
23
-
-
84976515556
-
Clamshell: Speeding up crowds for low-latency data labeling
-
D. Haas, J. Wang, E. Wu, and M. J. Franklin. Clamshell: Speeding up crowds for low-latency data labeling. PVLDB, 9(4):372-383, 2015.
-
(2015)
PVLDB
, vol.9
, Issue.4
, pp. 372-383
-
-
Haas, D.1
Wang, J.2
Wu, E.3
Franklin, M.J.4
-
24
-
-
84980390225
-
Crowdsourced poi labelling: Location-aware result inference and task assignment
-
H. Hu, Y. Zheng, Z. Bao, G. Li, J. Feng, and R. Cheng. Crowdsourced poi labelling: Location-aware result inference and task assignment. In ICDE, pages 61-72, 2016.
-
(2016)
ICDE
, pp. 61-72
-
-
Hu, H.1
Zheng, Y.2
Bao, Z.3
Li, G.4
Feng, J.5
Cheng, R.6
-
26
-
-
85162483531
-
Iterative learning for reliable crowdsourcing systems
-
D. R. Karger, S. Oh, and D. Shah. Iterative learning for reliable crowdsourcing systems. In NIPS, pages 1953-1961, 2011.
-
(2011)
NIPS
, pp. 1953-1961
-
-
Karger, D.R.1
Oh, S.2
Shah, D.3
-
27
-
-
84901947678
-
Bayesian classifier combination
-
H.-C. Kim and Z. Ghahramani. Bayesian classifier combination. In AISTATS, pages 619-627, 2012.
-
(2012)
AISTATS
, pp. 619-627
-
-
Kim, H.-C.1
Ghahramani, Z.2
-
29
-
-
84982126145
-
Crowdsourced data management: Asurvey
-
G. Li, J. Wang, Y. Zheng, and M. J. Franklin. Crowdsourced data management: Asurvey. TKDE, 28(9):2296-2319, 2016.
-
(2016)
TKDE
, vol.28
, Issue.9
, pp. 2296-2319
-
-
Li, G.1
Wang, J.2
Zheng, Y.3
Franklin, M.J.4
-
30
-
-
84938779276
-
A confidence-aware approach for truth discovery on long-tail data
-
Q. Li, Y. Li, J. Gao, L. Su, B. Zhao, M. Demirbas, W. Fan, and J. Han. A confidence-aware approach for truth discovery on long-tail data. PVLDB, 8(4):425-436, 2014.
-
(2014)
PVLDB
, vol.8
, Issue.4
, pp. 425-436
-
-
Li, Q.1
Li, Y.2
Gao, J.3
Su, L.4
Zhao, B.5
Demirbas, M.6
Fan, W.7
Han, J.8
-
31
-
-
84904367424
-
Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation
-
Q. Li, Y. Li, J. Gao, B. Zhao, W. Fan, and J. Han. Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation. In SIGMOD, pages 1187-1198, 2014.
-
(2014)
SIGMOD
, pp. 1187-1198
-
-
Li, Q.1
Li, Y.2
Gao, J.3
Zhao, B.4
Fan, W.5
Han, J.6
-
33
-
-
84877752474
-
Variational inference for crowdsourcing
-
Q. Liu, J. Peng, and A. T. Ihler. Variational inference for crowdsourcing. In NIPS, pages 692-700, 2012.
-
(2012)
NIPS
, pp. 692-700
-
-
Liu, Q.1
Peng, J.2
Ihler, A.T.3
-
34
-
-
84873191280
-
Cdas: A crowdsourcing data analytics system
-
X. Liu, M. Lu, B. C. Ooi, Y. Shen, S. Wu, and M. Zhang. Cdas: a crowdsourcing data analytics system. PVLDB, 5(10):1040-1051, 2012.
-
(2012)
PVLDB
, vol.5
, Issue.10
, pp. 1040-1051
-
-
Liu, X.1
Lu, M.2
Ooi, B.C.3
Shen, Y.4
Wu, S.5
Zhang, M.6
-
35
-
-
84954098959
-
Faitcrowd: Fine grained truth discovery for crowdsourced data aggregation
-
F. Ma, Y. Li, Q. Li, M. Qiu, J. Gao, S. Zhi, L. Su, B. Zhao, H. Ji, and J. Han. Faitcrowd: Fine grained truth discovery for crowdsourced data aggregation. In KDD, pages 745-754, 2015.
-
(2015)
KDD
, pp. 745-754
-
-
Ma, F.1
Li, Y.2
Li, Q.3
Qiu, M.4
Gao, J.5
Zhi, S.6
Su, L.7
Zhao, B.8
Ji, H.9
Han, J.10
-
36
-
-
84860851183
-
Human-powered sorts and joins
-
A. Marcus, E. Wu, D. R. Karger, S. Madden, and R. C. Miller. Human-powered sorts and joins. PVLDB, 5(1):13-24, 2011.
-
(2011)
PVLDB
, vol.5
, Issue.1
, pp. 13-24
-
-
Marcus, A.1
Wu, E.2
Karger, D.R.3
Madden, S.4
Miller, R.C.5
-
37
-
-
80053541967
-
Crowdsourced databases: Query processing with people
-
A. Marcus, E. Wu, S. Madden, and R. C. Miller. Crowdsourced databases: Query processing with people. In CIDR, pages 211-214, 2011.
-
(2011)
CIDR
, pp. 211-214
-
-
Marcus, A.1
Wu, E.2
Madden, S.3
Miller, R.C.4
-
38
-
-
84862645517
-
Crowdscreen: Algorithms for filtering data with humans
-
A. G. Parameswaran, H. Garcia-Molina, H. Park, N. Polyzotis, A. Ramesh, and J. Widom. Crowdscreen: Algorithms for filtering data with humans. In SIGMOD, pages 361-372, 2012.
-
(2012)
SIGMOD
, pp. 361-372
-
-
Parameswaran, A.G.1
Garcia-Molina, H.2
Park, H.3
Polyzotis, N.4
Ramesh, A.5
Widom, J.6
-
39
-
-
84871076960
-
Deco: Declarative crowdsourcing
-
A. G. Parameswaran, H. Park, H. Garcia-Molina, N. Polyzotis, and J. Widom. Deco: declarative crowdsourcing. In CIKM, pages 1203-1212, 2012.
-
(2012)
CIKM
, pp. 1203-1212
-
-
Parameswaran, A.G.1
Park, H.2
Garcia-Molina, H.3
Polyzotis, N.4
Widom, J.5
-
40
-
-
85020405143
-
-
Project Page. http://dbgroup.cs.tsinghua.edu.cn/ligl/crowd_truth_inference/.
-
-
-
-
41
-
-
77951954464
-
Learning from crowds
-
V. C. Raykar, S. Yu, L. H. Zhao, G. H. Valadez, C. Florin, L. Bogoni, and L. Moy. Learning from crowds. JMLR, 11(Apr):1297-1322, 2010.
-
(2010)
JMLR
, vol.11
, Issue.APR
, pp. 1297-1322
-
-
Raykar, V.C.1
Yu, S.2
Zhao, L.H.3
Valadez, G.H.4
Florin, C.5
Bogoni, L.6
Moy, L.7
-
42
-
-
0002947255
-
A mathematical theory of communication
-
C. E. Shannon. A mathematical theory of communication. SIGMOBILE Mob. Comput. Commun. Rev., 5(1):3-55, 2001.
-
(2001)
SIGMOBILE Mob. Comput. Commun. Rev
, vol.5
, Issue.1
, pp. 3-55
-
-
Shannon, C.E.1
-
43
-
-
84968863325
-
Language understanding in the wild: Combining crowdsourcing and machine learning
-
E. D. Simpson, M. Venanzi, S. Reece, P. Kohli, J. Guiver, S. J. Roberts, and N. R. Jennings. Language understanding in the wild: Combining crowdsourcing and machine learning. In WWW, pages 992-1002, 2015.
-
(2015)
WWW
, pp. 992-1002
-
-
Simpson, E.D.1
Venanzi, M.2
Reece, S.3
Kohli, P.4
Guiver, J.5
Roberts, S.J.6
Jennings, N.R.7
-
44
-
-
80053360508
-
Cheap and fast-but is it good?: Evaluating non-expert annotations for natural language tasks
-
R. Snow, B. O'Connor, D. Jurafsky, and A. Y. Ng. Cheap and fast-but is it good?: evaluating non-expert annotations for natural language tasks. In EMNLP, pages 254-263, 2008.
-
(2008)
EMNLP
, pp. 254-263
-
-
Snow, R.1
O'Connor, B.2
Jurafsky, D.3
Ng, A.Y.4
-
45
-
-
85020385776
-
-
Twitter Sentiment. http://www.sananalytics.com/lab/twitter-sentiment/.
-
-
-
-
46
-
-
84909581998
-
Community-based bayesian aggregation models for crowdsourcing
-
M. Venanzi, J. Guiver, G. Kazai, P. Kohli, and M. Shokouhi. Community-based bayesian aggregation models for crowdsourcing. In WWW, pages 155-164, 2014.
-
(2014)
WWW
, pp. 155-164
-
-
Venanzi, M.1
Guiver, J.2
Kazai, G.3
Kohli, P.4
Shokouhi, M.5
-
47
-
-
84860870463
-
Max algorithms in crowdsourcing environments
-
P. Venetis, H. Garcia-Molina, K. Huang, and N. Polyzotis. Max algorithms in crowdsourcing environments. In WWW, pages 989-998, 2012.
-
(2012)
WWW
, pp. 989-998
-
-
Venetis, P.1
Garcia-Molina, H.2
Huang, K.3
Polyzotis, N.4
-
48
-
-
51749107030
-
Recaptcha: Human-based character recognition via web security measures
-
L. Von Ahn, B. Maurer, C. McMillen, D. Abraham, and M. Blum. recaptcha: Human-based character recognition via web security measures. Science, 321(5895):1465-1468, 2008.
-
(2008)
Science
, vol.321
, Issue.5895
, pp. 1465-1468
-
-
Von Ahn, L.1
Maurer, B.2
McMillen, C.3
Abraham, D.4
Blum, M.5
-
49
-
-
65749118363
-
Graphical models, exponential families, and variational inference
-
M. J. Wainwright and M. I. Jordan. Graphical models, exponential families, and variational inference. Foundations and Trends in Machine Learning, 1(1-2):1-305, 2008.
-
(2008)
Foundations and Trends in Machine Learning
, vol.1
, Issue.1-2
, pp. 1-305
-
-
Wainwright, M.J.1
Jordan, M.I.2
-
50
-
-
84872946975
-
Crowder: Crowdsourcing entity resolution
-
J. Wang, T. Kraska, M. J. Franklin, and J. Feng. Crowder: Crowdsourcing entity resolution. PVLDB, 5(11):1483-1494, 2012.
-
(2012)
PVLDB
, vol.5
, Issue.11
, pp. 1483-1494
-
-
Wang, J.1
Kraska, T.2
Franklin, M.J.3
Feng, J.4
-
51
-
-
85162055266
-
The multidimensional wisdom of crowds
-
P. Welinder, S. Branson, P. Perona, and S. J. Belongie. The multidimensional wisdom of crowds. In NIPS, pages 2424-2432, 2010.
-
(2010)
NIPS
, pp. 2424-2432
-
-
Welinder, P.1
Branson, S.2
Perona, P.3
Belongie, S.J.4
-
52
-
-
84881231558
-
Question selection for crowd entity resolution
-
S. E. Whang, P. Lofgren, and H. Garcia-Molina. Question selection for crowd entity resolution. PVLDB, 6(6):349-360, 2013.
-
(2013)
PVLDB
, vol.6
, Issue.6
, pp. 349-360
-
-
Whang, S.E.1
Lofgren, P.2
Garcia-Molina, H.3
-
53
-
-
77951951247
-
Whose vote should count more: Optimal integration of labels from labelers of unknown expertise
-
J. Whitehill, T.-F. Wu, J. Bergsma, J. R. Movellan, and P. L. Ruvolo. Whose vote should count more: Optimal integration of labels from labelers of unknown expertise. In NIPS, pages 2035-2043, 2009.
-
(2009)
NIPS
, pp. 2035-2043
-
-
Whitehill, J.1
Wu, T.-F.2
Bergsma, J.3
Movellan, J.R.4
Ruvolo, P.L.5
-
54
-
-
80052400610
-
Modeling annotator expertise: Learning when everybody knows a bit of something
-
Y. Yan, R. Rosales, G. Fung, M. W. Schmidt, G. H. Valadez, L. Bogoni, L. Moy, and J. G. Dy. Modeling annotator expertise: Learning when everybody knows a bit of something. In AISTATS, pages 932-939, 2010.
-
(2010)
AISTATS
, pp. 932-939
-
-
Yan, Y.1
Rosales, R.2
Fung, G.3
Schmidt, M.W.4
Valadez, G.H.5
Bogoni, L.6
Moy, L.7
Dy, J.G.8
-
55
-
-
84975797359
-
Crowdsourced top-k algorithms: An experimental evaluation
-
X. Zhang, G. Li, and J. Feng. Crowdsourced top-k algorithms: An experimental evaluation. PVLDB, 9(8):612-623, 2016.
-
(2016)
PVLDB
, vol.9
, Issue.8
, pp. 612-623
-
-
Zhang, X.1
Li, G.2
Feng, J.3
-
56
-
-
84995774405
-
Comparing twitter and traditional media using topic models
-
W. X. Zhao, J. Jiang, J. Weng, J. He, E.-P. Lim, H. Yan, and X. Li. Comparing twitter and traditional media using topic models. In ECIR, pages 338-349. 2011.
-
(2011)
ECIR
, pp. 338-349
-
-
Zhao, W.X.1
Jiang, J.2
Weng, J.3
He, J.4
Lim, E.-P.5
Yan, H.6
Li, X.7
-
57
-
-
84976333362
-
Crowd-selection query processing in crowdsourcing databases: A task-driven approach
-
Z. Zhao, F. Wei, M. Zhou, W. Chen, and W. Ng. Crowd-selection query processing in crowdsourcing databases: A task-driven approach. EDBT, pages 397-408, 2015.
-
(2015)
EDBT
, pp. 397-408
-
-
Zhao, Z.1
Wei, F.2
Zhou, M.3
Chen, W.4
Ng, W.5
-
58
-
-
84976285854
-
On optimality of jury selection in crowdsourcing
-
Y. Zheng, R. Cheng, S. Maniu, and L. Mo. On optimality of jury selection in crowdsourcing. In EDBT, pages 193-204, 2015.
-
(2015)
EDBT
, pp. 193-204
-
-
Zheng, Y.1
Cheng, R.2
Maniu, S.3
Mo, L.4
-
59
-
-
85020440647
-
Docs: A domain-aware crowdsourcing system using knowledge bases
-
Y. Zheng, G. Li, and R. Cheng. Docs: a domain-aware crowdsourcing system using knowledge bases. PVLDB, 10(4):361-372, 2016.
-
(2016)
PVLDB
, vol.10
, Issue.4
, pp. 361-372
-
-
Zheng, Y.1
Li, G.2
Cheng, R.3
-
60
-
-
84957566214
-
Qasca: A quality-aware task assignment system for crowdsourcing applications
-
Y. Zheng, J. Wang, G. Li, R. Cheng, and J. Feng. Qasca: A quality-aware task assignment system for crowdsourcing applications. In SIGMOD, pages 1031-1046, 2015.
-
(2015)
SIGMOD
, pp. 1031-1046
-
-
Zheng, Y.1
Wang, J.2
Li, G.3
Cheng, R.4
Feng, J.5
-
61
-
-
84877729010
-
Learning from the wisdom of crowds by minimax entropy
-
D. Zhou, S. Basu, Y. Mao, and J. C. Platt. Learning from the wisdom of crowds by minimax entropy. In NIPS, pages 2195-2203, 2012.
-
(2012)
NIPS
, pp. 2195-2203
-
-
Zhou, D.1
Basu, S.2
Mao, Y.3
Platt, J.C.4
-
62
-
-
84979669863
-
Aggregating ordinal labels from crowds by minimax conditional entropy
-
D. Zhou, Q. Liu, J. Platt, and C. Meek. Aggregating ordinal labels from crowds by minimax conditional entropy. In ICML, pages 262-270, 2014.
-
(2014)
ICML
, pp. 262-270
-
-
Zhou, D.1
Liu, Q.2
Platt, J.3
Meek, C.4
-
63
-
-
0000806445
-
Minimax entropy principle and its application to texture modeling
-
S. Zhu, Y. Wu, and D. Mumford. Minimax entropy principle and its application to texture modeling. Neural computation, 9(8):1627-1660, 1997.
-
(1997)
Neural computation
, vol.9
, Issue.8
, pp. 1627-1660
-
-
Zhu, S.1
Wu, Y.2
Mumford, D.3
|