This imbalance can result in degraded performance in the presence of high quality or many annotations. 2.2 Confused Supervised LDA (CSLDA). We solve the�...

Corpus labeling projects frequently use low-cost workers from microtask market- places; however, these workers are often inexperienced or have misaligned�...

A novel crowdsourcing model is introduced that adapts the discrete supervised topic model sLDA to handle multiple corrupt, usually conflicting supervision�...

Feb 14, 2016 � Making the Most of Crowdsourced Document Annotations: Confused Supervised LDA. 599 ...
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Posted: Feb 14, 2016

Jul 22, 2015 � We introduce a novel crowdsourcing model that adapts the discrete supervised topic model sLDA to handle multiple corrupt, usually conflicting (�...

Making the Most of Crowdsourced Document Annotations: Confused Supervised LDA. CONLL 2015 � Paul Felt, Eric Ringger, Jordan Boyd-Graber, Kevin Seppi �

Making the Most of Crowdsourced Document Annotations: Confused Supervised LDA � Felt Paul � Ringger Eric � Boyd-Graber Jordan � Seppi Kevin.

Making the Most of Crowdsourced Document Annotations: Confused Supervised LDA. Paul Felt | Eric Ringger | Jordan Boyd-Graber | Kevin Seppi |. Paper Details:.

[Supervised machine learning] Supervised learning is the machine learning task of inferring a function from labeled training data. The training data consist of�...

Making the Most of Crowdsourced Document Annotations: Confused Supervised LDA (2015) Felt, Paul and Ringger, Eric and Boyd-Graber, Jordan and Seppi, Kevin.