Person: Yue Shi

DBLP: Shi:Yue

Contributed to:

2015

2014

2014

2013

2012

2012

2011

2010

2009

Wrote 12 papers:

KDD-2015-ZhongLSR #recommendation #scalability

Building Discriminative User Profiles for Large-scale Content Recommendation (EZ, NL, YS, SR), pp. 2277–2286.

CIKM-2014-ShiKBLH #learning #named #recommendation

CARS2: Learning Context-aware Representations for Context-aware Recommendations (YS, AK, LB, ML, AH), pp. 291–300.

ECIR-2014-LoniSLH #collaboration

Cross-Domain Collaborative Filtering with Factorization Machines (BL, YS, ML, AH), pp. 656–661.

RecSys-2013-KaratzoglouBS #learning #rank #recommendation

Learning to rank for recommender systems (AK, LB, YS), pp. 493–494.

RecSys-2013-ShiKBLH #multi #named #optimisation #rank

xCLiMF: optimizing expected reciprocal rank for data with multiple levels of relevance (YS, AK, LB, ML, AH), pp. 431–434.

RecSys-2012-ShiKBLOH #collaboration #learning #named #rank

CLiMF: learning to maximize reciprocal rank with collaborative less-is-more filtering (YS, AK, LB, ML, NO, AH), pp. 139–146.

SIGIR-2012-ShiKBLHO #named #optimisation #recommendation

TFMAP: optimizing MAP for top-n context-aware recommendation (YS, AK, LB, ML, AH, NO), pp. 155–164.

SIGIR-2012-ShiZWLH #adaptation #recommendation

Adaptive diversification of recommendation results via latent factor portfolio (YS, XZ, JW, ML, AH), pp. 175–184.

ECIR-2011-ShiLH #collaboration #multi #ranking #self

Reranking Collaborative Filtering with Multiple Self-contained Modalities (YS, ML, AH), pp. 699–703.

ECIR-2011-ShiLH11a #how #question #recommendation #trust

How Far Are We in Trust-Aware Recommendation? (YS, ML, AH), pp. 704–707.

RecSys-2010-ShiLH #collaboration #learning #matrix #rank

List-wise learning to rank with matrix factorization for collaborative filtering (YS, ML, AH), pp. 269–272.

RecSys-2009-ShiLH #collaboration #similarity

Exploiting user similarity based on rated-item pools for improved user-based collaborative filtering (YS, ML, AH), pp. 125–132.