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Efficient Crowdsourcing for Multi-class Labeling

ACM SIGMETRICS Performance Evaluation Review
2013-06
203
小木 发布于 2017/02/07 10:30:31
信息融合,多标签融合,众包

Variational Inference for Crowdsourcing

NIPS
2012-11
345
小木 发布于 2017/02/07 09:39:17
信息融合,群体智慧,BP

Bagging Predictors

Machine Learning
1996-07
245
小木 发布于 2017/02/06 09:58:08
融合算法,融合信息

Forecast aggregation via recalibration

Machine Learning
2014-06
228
小木 发布于 2017/02/06 09:57:52
群体智慧,信息融合

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

Management Science
2014-03
240
小木 发布于 2017/02/06 09:57:43
群体智慧,信息融合

Unanimity and compromise among probability forecasters

Management science
1990-07
200
小木 发布于 2017/02/06 09:57:33
预测,群体智慧,信息融合

A solution to the single-question crowd wisdom problem

Nature
2017-01
391
小木 发布于 2017/02/06 09:57:16
信息融合,群体智慧

Optimizing Semantic Coherence in Topic Models

EMNLP
2011-07
288
小木 发布于 2017/02/06 09:57:05
主题模型,LDA,主题模型评价

A Biterm Topic Model for Short Texts

WWW
2013-05
477
小木 发布于 2017/02/06 09:56:52
主题模型,LDA

Improving Topic Coherence with Regularized Topic Models

NIPS
2011-09
175
小木 发布于 2017/02/06 09:56:42
主题模型,LDA,正则项

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

KDD
2014-08
179
小木 发布于 2017/02/06 09:56:28
LDA,主题模型

Discovering Coherent Topics Using General Knowledge

CIKM
2013-09
230
小木 发布于 2017/02/06 09:56:15
LDA,主题模型,领域知识

Incorporating Domain Knowledge into Topic Modeling via Dirichlet Forest Priors

ICML
2009-09
192
小木 发布于 2017/02/06 09:55:50
主题模型,领域知识

Interactive Topic Modeling

Machine Learning
2014-06
327
小木 发布于 2017/02/06 09:55:36
LDA,人机交互,主题模型

Learning from multiple annotators with varying expertise

Machine Learning
2014-06
191
小木 发布于 2017/02/06 09:55:17
信息融合,群体智慧