Making the Most of Crowdsourced Document Annotations: Confused Supervised LDA

CoNLL
2015-09
2629
小木 发布于 2017/02/06 09:46:55
LDA,主题模型,信息融合

Learning from multiple annotators with varying expertise

Machine Learning
2014-06
2073
小木 发布于 2017/02/06 09:55:17
信息融合,群体智慧

Interactive Topic Modeling

Machine Learning
2014-06
2266
小木 发布于 2017/02/06 09:55:36
LDA,人机交互,主题模型

Incorporating Domain Knowledge into Topic Modeling via Dirichlet Forest Priors

ICML
2009-09
1896
小木 发布于 2017/02/06 09:55:50
主题模型,领域知识

Discovering Coherent Topics Using General Knowledge

CIKM
2013-09
2197
小木 发布于 2017/02/06 09:56:15
LDA,主题模型,领域知识

Mining Topics in Documents: Standing on the Shoulders of Big Data

KDD
2014-08
2060
小木 发布于 2017/02/06 09:56:28
LDA,主题模型

Improving Topic Coherence with Regularized Topic Models

NIPS
2011-09
2041
小木 发布于 2017/02/06 09:56:42
主题模型,LDA,正则项

A Biterm Topic Model for Short Texts

WWW
2013-05
7635
小木 发布于 2017/02/06 09:56:52
主题模型,LDA

Optimizing Semantic Coherence in Topic Models

EMNLP
2011-07
4336
小木 发布于 2017/02/06 09:57:05
主题模型,LDA,主题模型评价

A solution to the single-question crowd wisdom problem

Nature
2017-01
2873
小木 发布于 2017/02/06 09:57:16
信息融合,群体智慧

Unanimity and compromise among probability forecasters

Management science
1990-07
2078
小木 发布于 2017/02/06 09:57:33
预测,群体智慧,信息融合

Identifying expertise and using it to extract the Wisdom of the Crowds

Management Science
2014-03
2206
小木 发布于 2017/02/06 09:57:43
群体智慧,信息融合

Forecast aggregation via recalibration

Machine Learning
2014-06
2006
小木 发布于 2017/02/06 09:57:52
群体智慧,信息融合

Bagging Predictors

Machine Learning
1996-07
2870
小木 发布于 2017/02/06 09:58:08
融合算法,融合信息

Variational Inference for Crowdsourcing

NIPS
2012-11
2457
小木 发布于 2017/02/07 09:39:17
信息融合,群体智慧,BP