Economic Recommendation with Surplus Maximization

2016 International Conference on World Wide Web
2016-04
2621
Vanessa He 发布于 2017/11/23 15:54:05
Total Surplus Maximization,Online Service Allocation,Computational Economics,Recommendation Systems; Web-based Services

Making the Most of Crowdsourced Document Annotations: Confused Supervised LDA

CoNLL
2015-09
2623
小木 发布于 2017/02/06 09:46:55
LDA,主题模型,信息融合

Topic Modeling: Beyond Bag-of-Words

ICML
2006-09
2745
小木 发布于 2017/05/05 21:24:45
LDA,主题模型

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

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

Bagging Predictors

Machine Learning
1996-07
2868
小木 发布于 2017/02/06 09:58:08
融合算法,融合信息

A solution to the single-question crowd wisdom problem

Nature
2017-01
2871
小木 发布于 2017/02/06 09:57:16
信息融合,群体智慧

Multilevel Bayesian Models of Categorical Data Annotation

Unpublished manuscript
2008-09
3008
小木 发布于 2017/05/14 23:58:14
数据标注,信息融合,贝叶斯,统计

Crowdsourced Data Management: A Survey

TKDE
2016-09
3049
小木 发布于 2017/04/20 20:50:51
众包,信息融合,综述

Learning From Crowds

Journal of Machine Learning Research
2010-10
3157
小木 发布于 2017/05/14 23:57:48
信息融合,众包,数据标注

Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering

WWW
2016-09
3163
Vanessa He 发布于 2017/05/23 16:46:14
Recommender Systems,Fashion Evolution,Personalized Ranking,Visual Dimensions

Syntactic Topic Models

NIPS
2009-09
3271
小木 发布于 2017/05/06 09:55:27
LDA,主题模型,非词袋模型,非参数模型

Collaborative Filtering for Implicit Feedback Datasets

协同过滤,隐式反馈,WRMF

A Partial-Order-Based Model to Estimate Individual Preferences using Panel Data

Management Science
2017-04
3414
Vanessa He 发布于 2017/06/15 20:17:08
nonparametric choice models,inertia in choice,brand loyalty,panel data,partial-orders,customized promotions ,personalized predictions

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

BPR: Bayesian Personalized Ranking from Implicit Feedback

Conference on Uncertainty in Artificial Intelligence
2009-12
3708
Vanessa He 发布于 2017/02/27 21:06:29
个性化排序,贝叶斯优化准则,LearnBPR学习算法,矩阵分解,BPRMF