-
1
-
-
0003102944
-
Maximum likelihood estimation of observer error-rates using em algorithm
-
A. P. Dawid and A. M. Skene. Maximum likelihood estimation of observer error-rates using em algorithm. Appl. Statist., 28(1):20-28, 1979.
-
(1979)
Appl. Statist.
, vol.28
, Issue.1
, pp. 20-28
-
-
Dawid, A.P.1
Skene, A.M.2
-
2
-
-
0015865168
-
Time bounds for selection
-
M. Blum, R. W. Floyd, V. R. Pratt, R. L. Rivest, and R. E. Time bounds for selection. Journal of Computer and System Sciences, 7(4):448-461, 1973.
-
(1973)
Journal of Computer and System Sciences
, vol.7
, Issue.4
, pp. 448-461
-
-
Blum, M.1
Floyd, R.W.2
Pratt, V.R.3
Rivest, R.L.4
Ri, E.5
-
3
-
-
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, 2012.
-
(2012)
ICDE
-
-
Boim, R.1
Greenshpan, O.2
Milo, T.3
Novgorodov, S.4
Polyzotis, N.5
Tan, W.C.6
-
5
-
-
84874248579
-
Pairwise ranking aggregation in a crowdsourced setting
-
X. Chen, P. N. Bennett, K. Collins-Thompson, and E. Horvitz. Pairwise ranking aggregation in a crowdsourced setting. In WSDM, pages 193-202, 2013.
-
(2013)
WSDM
, pp. 193-202
-
-
Chen, X.1
Bennett, P.N.2
Collins-Thompson, K.3
Horvitz, E.4
-
6
-
-
84901398917
-
Optimistic knowledge gradient policy for optimal budget allocation in crowdsourcing
-
X. Chen, Q. Lin, and D. Zhou. Optimistic knowledge gradient policy for optimal budget allocation in crowdsourcing. In ICML, pages 64-72, 2013.
-
(2013)
ICML
, pp. 64-72
-
-
Chen, X.1
Lin, Q.2
Zhou, D.3
-
7
-
-
84857558347
-
On using crowdsourcing and active learning to improve classification performance
-
J. Costa, C. Silva, M. Antunes, and B. Ribeiro. On using crowdsourcing and active learning to improve classification performance. In ISDA, 2011.
-
(2011)
ISDA
-
-
Costa, J.1
Silva, C.2
Antunes, M.3
Ribeiro, B.4
-
8
-
-
84880360544
-
Pomdp-based control of workflows for crowdsourcing
-
P. Dai, C. H. Lin, Mausam, and D. S. Weld. Pomdp-based control of workflows for crowdsourcing. Artif. Intell., 202:52-85, 2013.
-
(2013)
Artif. Intell.
, vol.202
, pp. 52-85
-
-
Dai, P.1
Lin, C.H.2
Mausam3
Weld, D.S.4
-
9
-
-
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
-
10
-
-
0002629270
-
Maximum likelihood from incomplete data via the em algorithm
-
A. P. Dempster, N. M. Laird, and D. B. Rubin. Maximum likelihood from incomplete data via the em algorithm. J. R. Statist. Soc. B, 30(1):1-38, 1977.
-
(1977)
J. R. Statist. Soc. B
, vol.30
, Issue.1
, pp. 1-38
-
-
Dempster, A.P.1
Laird, N.M.2
Rubin, D.B.3
-
11
-
-
84901786293
-
Massjoin: A mapreduce-based method for scalable string similarity joins
-
D. Deng, G. Li, S. Hao, J. Wang, and J. Feng. Massjoin: A mapreduce-based method for scalable string similarity joins. In ICDE, pages 340-351, 2014.
-
(2014)
ICDE
, pp. 340-351
-
-
Deng, D.1
Li, G.2
Hao, S.3
Wang, J.4
Feng, J.5
-
12
-
-
0000181889
-
On nonlinear fractional programming
-
March, 1967
-
W. Dinkelbach. On nonlinear fractional programming. Management Science, 13(7):492-498, March, 1967.
-
Management Science
, vol.13
, Issue.7
, pp. 492-498
-
-
Dinkelbach, W.1
-
13
-
-
30344451668
-
Weighted random sampling with a reservoir
-
P. Efraimidis and P. G. Spirakis. Weighted random sampling with a reservoir. Inf. Process. Lett., 97(5):181-185, 2006.
-
(2006)
Inf. Process. Lett.
, vol.97
, Issue.5
, pp. 181-185
-
-
Efraimidis, P.1
Spirakis, P.G.2
-
14
-
-
79959958767
-
Crowddb: Answering queries with crowdsourcing
-
M. J. Franklin, D. Kossmann, T. Kraska, S. Ramesh, and R. Xin. Crowddb: answering queries with crowdsourcing. In SIGMOD Conference, 2011.
-
(2011)
SIGMOD Conference
-
-
Franklin, M.J.1
Kossmann, D.2
Kraska, T.3
Ramesh, S.4
Xin, R.5
-
15
-
-
84880542053
-
An online cost sensitive decision-making method in crowdsourcing systems
-
J. Gao, X. Liu, B. C. Ooi, H. Wang, and G. Chen. An online cost sensitive decision-making method in crowdsourcing systems. In SIGMOD, 2013.
-
(2013)
SIGMOD
-
-
Gao, J.1
Liu, X.2
Ooi, B.C.3
Wang, H.4
Chen, G.5
-
17
-
-
84877979429
-
Combining crowdsourcing and google street view to identify street-level accessibility problems
-
K. Hara, V. Le, and J. Froehlich. Combining crowdsourcing and google street view to identify street-level accessibility problems. In CHI, 2013.
-
(2013)
CHI
-
-
Hara, K.1
Le, V.2
Froehlich, J.3
-
18
-
-
84897504552
-
Adaptive task assignment for crowdsourced classification
-
C.-J. Ho, S. Jabbari, and J. W. Vaughan. Adaptive task assignment for crowdsourced classification. In ICML (1), pages 534-542, 2013.
-
(2013)
ICML
, Issue.1
, pp. 534-542
-
-
Ho, C.-J.1
Jabbari, S.2
Vaughan, J.W.3
-
19
-
-
84886397297
-
Online task assignment in crowdsourcing markets
-
C.-J. Ho and J. W. Vaughan. Online task assignment in crowdsourcing markets. In AAAI, 2012.
-
(2012)
AAAI
-
-
Ho, C.-J.1
Vaughan, J.W.2
-
21
-
-
84887447348
-
An evaluation of aggregation techniques in crowdsourcing
-
Springer
-
N. Q. V. Hung, N. T. Tam, L. N. Tran, and K. Aberer. An evaluation of aggregation techniques in crowdsourcing. In WISE, pages 1-15. Springer, 2013.
-
(2013)
WISE
, pp. 1-15
-
-
Hung, N.Q.V.1
Tam, N.T.2
Tran, L.N.3
Aberer, K.4
-
22
-
-
77956245055
-
Quality management on amazon mechanical turk
-
P. Ipeirotis, F. Provost, and J. Wang. Quality management on amazon mechanical turk. In SIGKDD workshop, pages 64-67, 2010.
-
(2010)
SIGKDD Workshop
, pp. 64-67
-
-
Ipeirotis, P.1
Provost, F.2
Wang, J.3
-
23
-
-
79958122721
-
Analyzing the amazon mechanical turk marketplace
-
P. G. Ipeirotis. Analyzing the amazon mechanical turk marketplace. ACM Crossroads, 17(2):16-21, 2010.
-
(2010)
ACM Crossroads
, vol.17
, Issue.2
, pp. 16-21
-
-
Ipeirotis, P.G.1
-
24
-
-
66549104913
-
A maximum expected utility framework for binary sequence labeling
-
M. Jansche. A maximum expected utility framework for binary sequence labeling. In ACL, 2007.
-
(2007)
ACL
-
-
Jansche, M.1
-
25
-
-
57149131807
-
Pay-as-you-go user feedback for dataspace systems
-
S. R. Jeffery, M. J. Franklin, and A. Y. Halevy. Pay-as-you-go user feedback for dataspace systems. In SIGMOD, pages 847-860, 2008.
-
(2008)
SIGMOD
, pp. 847-860
-
-
Jeffery, S.R.1
Franklin, M.J.2
Halevy, A.Y.3
-
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
-
-
59249096513
-
Keeping a digital library clean: New solutions to old problems
-
ACM
-
A. H. Laender, M. A. Gonçalves, R. G. Cota, A. A. Ferreira, R. L. T. Santos, and A. J. Silva. Keeping a digital library clean: New solutions to old problems. In DocEng, pages 257-262. ACM, 2008.
-
(2008)
DocEng
, pp. 257-262
-
-
Laender, A.H.1
Gonçalves, M.A.2
Cota, R.G.3
Ferreira, A.A.4
Santos, R.L.T.5
Silva, A.J.6
-
28
-
-
0029193061
-
Evaluating and optimizing autonomous text classification systems
-
D. D. Lewis. Evaluating and optimizing autonomous text classification systems. In SIGIR, pages 246-254, 1995.
-
(1995)
SIGIR
, pp. 246-254
-
-
Lewis, D.D.1
-
29
-
-
84875119323
-
Truth finding on the deep web: Is the problem solved?
-
X. Li, X. L. Dong, K. Lyons, W. Meng, and D. Srivastava. Truth finding on the deep web: Is the problem solved? PVLDB, 6(2):97-108, 2012.
-
(2012)
PVLDB
, vol.6
, Issue.2
, pp. 97-108
-
-
Li, X.1
Dong, X.L.2
Lyons, K.3
Meng, W.4
Srivastava, D.5
-
30
-
-
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
-
33
-
-
84875121323
-
Counting with the crowd
-
A. Marcus, D. R. Karger, S. Madden, R. Miller, and S. Oh. Counting with the crowd. PVLDB, 6(2):109-120, 2012.
-
(2012)
PVLDB
, vol.6
, Issue.2
, pp. 109-120
-
-
Marcus, A.1
Karger, D.R.2
Madden, S.3
Miller, R.4
Oh, S.5
-
34
-
-
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
-
35
-
-
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
-
36
-
-
79960270026
-
Evaluating entity resolution results
-
D. Menestrina, S. E. Whang, and H. Garcia-Molina. Evaluating entity resolution results. PVLDB, 3(1-2):208-219, 2010.
-
(2010)
PVLDB
, vol.3
, Issue.1-2
, pp. 208-219
-
-
Menestrina, D.1
Whang, S.E.2
Garcia-Molina, H.3
-
37
-
-
84916196366
-
Cross-task crowdsourcing
-
K. Mo, E. Zhong, and Q. Yang. Cross-task crowdsourcing. In KDD, 2013.
-
(2013)
KDD
-
-
Mo, K.1
Zhong, E.2
Yang, Q.3
-
38
-
-
84889595454
-
Optimizing plurality for human intelligence tasks
-
L. Mo, R. Cheng, B. Kao, X. S. Yang, C. Ren, S. Lei, D. W. Cheung, and E. Lo. Optimizing plurality for human intelligence tasks. In CIKM, 2013.
-
(2013)
CIKM
-
-
Mo, L.1
Cheng, R.2
Kao, B.3
Yang, X.S.4
Ren, C.5
Lei, S.6
Cheung, D.W.7
Lo, E.8
-
39
-
-
84911411712
-
Optimal decisions from probabilistic models: The intersection-over-union case
-
S. Nowozin. Optimal decisions from probabilistic models: the intersection-over-union case. In CVPR, 2014.
-
(2014)
CVPR
-
-
Nowozin, S.1
-
40
-
-
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 Conference, pages 361-372, 2012.
-
(2012)
SIGMOD Conference
, pp. 361-372
-
-
Parameswaran, A.G.1
Garcia-Molina, H.2
Park, H.3
Polyzotis, N.4
Ramesh, A.5
Widom, J.6
-
41
-
-
84873126754
-
Deco: A system for declarative crowdsourcing
-
H. Park, R. Pang, A. G. Parameswaran, H. Garcia-Molina, N. Polyzotis, and J. Widom. Deco: A system for declarative crowdsourcing. PVLDB, 5(12), 2012.
-
(2012)
PVLDB
, vol.5
, Issue.12
-
-
Park, H.1
Pang, R.2
Parameswaran, A.G.3
Garcia-Molina, H.4
Polyzotis, N.5
Widom, J.6
-
42
-
-
84904287648
-
Fusing data with correlations
-
R. Pochampally, A. D. Sarma, X. L. Dong, A. Meliou, and D. Srivastava. Fusing data with correlations. In SIGMOD, pages 433-444, 2014.
-
(2014)
SIGMOD
, pp. 433-444
-
-
Pochampally, R.1
Sarma, A.D.2
Dong, X.L.3
Meliou, A.4
Srivastava, D.5
-
43
-
-
85162536261
-
Ranking annotators for crowdsourced labeling tasks
-
V. C. Raykar and S. Yu. Ranking annotators for crowdsourced labeling tasks. In NIPS, pages 1809-1817, 2011.
-
(2011)
NIPS
, pp. 1809-1817
-
-
Raykar, V.C.1
Yu, S.2
-
44
-
-
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. Journal of Machine Learning Research, 2010.
-
(2010)
Journal of Machine Learning Research
-
-
Raykar, V.C.1
Yu, S.2
Zhao, L.H.3
Valadez, G.H.4
Florin, C.5
Bogoni, L.6
Moy, L.7
-
45
-
-
55149087864
-
A stochastic version of the price equation reveals the interplay of deterministic and stochastic processes in evolution
-
S. H. Rice. A stochastic version of the price equation reveals the interplay of deterministic and stochastic processes in evolution. BMC evolutionary biology, 8:262, 2008.
-
(2008)
BMC Evolutionary Biology
, vol.8
, pp. 262
-
-
Rice, S.H.1
-
46
-
-
84858389310
-
Crowdsourcing the evaluation of a domain-adapted named entity recognition system
-
A. B. Sayeed, T. J. Meyer, H. C. Nguyen, O. Buzek, and A. Weinberg. Crowdsourcing the evaluation of a domain-adapted named entity recognition system. In HLT-NAACL, pages 345-348, 2010.
-
(2010)
HLT-NAACL
, pp. 345-348
-
-
Sayeed, A.B.1
Meyer, T.J.2
Nguyen, H.C.3
Buzek, O.4
Weinberg, A.5
-
47
-
-
65449144451
-
Get another label? Improving data quality and data mining using multiple, noisy labelers
-
V. S. Sheng, F. J. Provost, and P. G. Ipeirotis. Get another label? improving data quality and data mining using multiple, noisy labelers. In KDD, 2008.
-
(2008)
KDD
-
-
Sheng, V.S.1
Provost, F.J.2
Ipeirotis, P.G.3
-
50
-
-
84880541670
-
Crowdsourced enumeration queries
-
B. Trushkowsky, T. Kraska, M. J. Franklin, and P. Sarkar. Crowdsourced enumeration queries. In ICDE, pages 673-684, 2013.
-
(2013)
ICDE
, pp. 673-684
-
-
Trushkowsky, B.1
Kraska, T.2
Franklin, M.J.3
Sarkar, P.4
-
52
-
-
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, 2014.
-
(2014)
WWW
-
-
Venanzi, M.1
Guiver, J.2
Kazai, G.3
Kohli, P.4
Shokouhi, M.5
-
54
-
-
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
-
55
-
-
77954744650
-
Efficient parallel set-similarity joins using mapreduce
-
ACM
-
R. Vernica, M. J. Carey, and C. Li. Efficient parallel set-similarity joins using mapreduce. In SIGMOD, pages 495-506. ACM, 2010.
-
(2010)
SIGMOD
, pp. 495-506
-
-
Vernica, R.1
Carey, M.J.2
Li, C.3
-
56
-
-
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
-
57
-
-
84904301041
-
A sample-and-clean framework for fast and accurate query processing on dirty data
-
ACM
-
J. Wang, S. Krishnan, M. J. Franklin, K. Goldberg, T. Kraska, and T. Milo. A sample-and-clean framework for fast and accurate query processing on dirty data. In SIGMOD, pages 469-480. ACM, 2014.
-
(2014)
SIGMOD
, pp. 469-480
-
-
Wang, J.1
Krishnan, S.2
Franklin, M.J.3
Goldberg, K.4
Kraska, T.5
Milo, T.6
-
58
-
-
84862702293
-
Can we beat the prefix filtering?: An adaptive framework for similarity join and search
-
J. Wang, G. Li, and J. Feng. Can we beat the prefix filtering?: an adaptive framework for similarity join and search. In SIGMOD, pages 85-96, 2012.
-
(2012)
SIGMOD
, pp. 85-96
-
-
Wang, J.1
Li, G.2
Feng, J.3
-
59
-
-
84880551539
-
Leveraging transitive relations for crowdsourced joins
-
J. Wang, G. Li, T. Kraska, M. J. Franklin, and J. Feng. Leveraging transitive relations for crowdsourced joins. In SIGMOD, 2013.
-
(2013)
SIGMOD
-
-
Wang, J.1
Li, G.2
Kraska, T.3
Franklin, M.J.4
Feng, J.5
-
60
-
-
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
-
61
-
-
77951951247
-
Whose vote should count more: Optimal integration of labels from labelers of unknown expertise
-
J. Whitehill, P. Ruvolo, T. Wu, J. Bergsma, and J. R. Movellan. 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
Ruvolo, P.2
Wu, T.3
Bergsma, J.4
Movellan, J.R.5
-
62
-
-
84882729189
-
Reducing uncertainty of schema matching via crowdsourcing
-
C. J. Zhang, L. Chen, H. V. Jagadish, and C. C. Cao. Reducing uncertainty of schema matching via crowdsourcing. PVLDB, 6(9):757-768, 2013.
-
(2013)
PVLDB
, vol.6
, Issue.9
, pp. 757-768
-
-
Zhang, C.J.1
Chen, L.2
Jagadish, H.V.3
Cao, C.C.4
-
63
-
-
84863769781
-
A Bayesian approach to discovering truth from conflicting sources for data integration
-
B. Zhao, B. I. Rubinstein, J. Gemmell, and J. Han. A bayesian approach to discovering truth from conflicting sources for data integration. PVLDB, 2012.
-
(2012)
PVLDB
-
-
Zhao, B.1
Rubinstein, B.I.2
Gemmell, J.3
Han, J.4
|