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

Explicit factor models for explainable recommendation based on phrase-level sentiment analysis

ACM
2014-07
3611
Vanessa He 发布于 2017/10/16 09:46:29
Recommender Systems,Sentiment Analysis,Collaborative Filtering,Recommendation Explanation

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

Forecast aggregation via recalibration

Machine Learning
2014-06
2001
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
2206
小木 发布于 2017/02/06 09:57:43
群体智慧,信息融合

Exploring Temporal Effects for Location Recommendation on Location-Based Social Networks

RecSys
2013-11
2537
Vanessa He 发布于 2017/06/08 21:55:42
Location Recommendation, Location-Based Social Networks, Temporal Effects

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

Point-of-Interest Recommendation in Location Based Social Networks with Topic and Location Awareness

Location-Based Social Networks, Recom- mender systems, Topic modeling

Informational Friend Recommendation in Social Media

SIGIR
2013-07
2143
Vanessa He 发布于 2017/06/08 21:39:20
Friend Recommendation, Informational Utility, Diversity

Efficient Crowdsourcing for Multi-class Labeling

ACM SIGMETRICS Performance Evaluation Review
2013-06
2114
小木 发布于 2017/02/07 10:30:31
信息融合,多标签融合,众包

A Biterm Topic Model for Short Texts

WWW
2013-05
7620
小木 发布于 2017/02/06 09:56:52
主题模型,LDA

Variational Inference for Crowdsourcing

NIPS
2012-11
2455
小木 发布于 2017/02/07 09:39:17
信息融合,群体智慧,BP

Multi-Relational Matrix Factorization using Bayesian Personalized Ranking for Social Network Data

MRBPR,Recommender Systems, Cold-Start, Multi-Relational Learn-ing, Social Network, Matrix Factorization, Item Prediction, Item Recommendation, Ranking, Joint Factorization

Crowdclustering

NIPS
2011-09
1595
小木 发布于 2017/04/22 10:40:50
众包,聚类