BibSLEIGH — Hui

Travelled to:

1 × Australia
1 × Canada
1 × Chile
1 × France
1 × Germany
1 × Ireland
1 × Singapore
1 × United Kingdom
14 × USA
2 × China

Collaborated with:

Y.Ge E.Chen J.Chen H.Zhu J.Wu W.Zhou Q.Liu V.Kumar C.Liu P.Luo H.Cao A.Tuzhilin M.Steinbach Y.Fu F.Zhuang Q.He P.Tan S.Shekhar Z.Yao T.Qian J.Tian Z.Shi J.Liu G.Liu Y.Xiong Z.Zhou K.Xiao B.Xiang F.Wang J.Hu B.Liu C.H.Q.Ding J.Yang X.Quan Q.Luo K.Lü W.Tang S.Zhong J.Wu P.Wu Y.Wang Y.Huang J.Pei K.Zhang G.Jiang Q.Yang M.Qu C.Luo Y.Guo G.Deng T.Hu S.Y.Sung H.Luo B.J.Gao M.Ester J.Cai O.Schulte J.Sun Y.Xiong Y.Zhu C.Guan B.Chang C.Tan X.Jin C.Du F.Tang J.X.Yu Y.Zheng W.Geng M.Perkins H.T.Ozdemir J.Yu K.C.Lee M.Gruteser M.J.Pazzani Q.Li B.Liu J.Srivastava P.C.Sheu R.K.Sahoo X.Gao W.Wu J.Ye Q.Li H.Park R.Janardan S.Papadimitriou C.Zhu T.Bao Y.Zheng Z.Shen

Talks about:

recommend (8) perspect (6) cluster (6) learn (6) multi (5) rank (5) support (4) exploit (4) system (4) enhanc (4)

Person: Hui Xiong

DBLP: Xiong:Hui

Contributed to:

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

Wrote 44 papers:

KDD-2015-FuLPXGZZ #modelling #ranking: Real Estate Ranking via Mixed Land-use Latent Models (YF, GL, SP, HX, YG, HZ, CZ), pp. 299–308.
KDD-2015-LiuWHX #framework #graph #health: Temporal Phenotyping from Longitudinal Electronic Health Records: A Graph Based Framework (CL, FW, JH, HX), pp. 705–714.
SIGIR-2015-SunXZLGX #multi #personalisation #recommendation: Multi-source Information Fusion for Personalized Restaurant Recommendation (JS, YX, YZ, JL, CG, HX), pp. 983–986.
CIKM-2014-ChangZGCXT #modelling #online #predict: Predicting the Popularity of Online Serials with Autoregressive Models (BC, HZ, YG, EC, HX, CT), pp. 1339–1348.
CIKM-2014-JinZXDLH #learning #multi: Multi-task Multi-view Learning for Heterogeneous Tasks (XJ, FZ, HX, CD, PL, QH), pp. 441–450.
CIKM-2014-LiuXCXTY #approach #bound #linear #network #scalability #social: Influence Maximization over Large-Scale Social Networks: A Bounded Linear Approach (QL, BX, EC, HX, FT, JXY), pp. 171–180.
KDD-2014-FuXGYZZ #clustering #dependence #ranking: Exploiting geographic dependencies for real estate appraisal: a mutual perspective of ranking and clustering (YF, HX, YG, ZY, YZ, ZHZ), pp. 1047–1056.
KDD-2014-LiuGXXGP #modelling #probability #process #workflow: Proactive workflow modeling by stochastic processes with application to healthcare operation and management (CL, YG, HX, KX, WG, MP), pp. 1593–1602.
KDD-2014-LiuZXJ0 #categorisation #visualisation: Temporal skeletonization on sequential data: patterns, categorization, and visualization (CL, KZ, HX, GJ, QY), pp. 1336–1345.
KDD-2014-QuZLLX #effectiveness #recommendation: A cost-effective recommender system for taxi drivers (MQ, HZ, JL, GL, HX), pp. 45–54.
KDD-2014-ZhuXGC #mobile #privacy #recommendation #security: Mobile app recommendations with security and privacy awareness (HZ, HX, YG, EC), pp. 951–960.
CIKM-2013-ZhuXGC #detection #mobile #perspective #ranking: Ranking fraud detection for mobile apps: a holistic view (HZ, HX, YG, EC), pp. 619–628.
KDD-2013-LiuFYX #learning #recommendation: Learning geographical preferences for point-of-interest recommendation (BL, YF, ZY, HX), pp. 1043–1051.
CIKM-2012-ZhuCCXT #classification #information management #mobile: Exploiting enriched contextual information for mobile app classification (HZ, HC, EC, HX, JT), pp. 1617–1621.
RecSys-2012-LiuXCGXBZ #recommendation: Influential seed items recommendation (QL, BX, EC, YG, HX, TB, YZ), pp. 245–248.
CIKM-2011-ZhuCXCT #category theory #ranking #towards: Towards expert finding by leveraging relevant categories in authority ranking (HZ, HC, HX, EC, JT), pp. 2221–2224.
KDD-2011-GeLXC: A taxi business intelligence system (YG, CL, HX, JC), pp. 735–738.
KDD-2011-GeLXTC #cost analysis #recommendation: Cost-aware travel tour recommendation (YG, QL, HX, AT, JC), pp. 983–991.
KDD-2011-LuoXZGD #composition #perspective: Enhancing investment decisions in P2P lending: an investor composition perspective (CL, HX, WZ, YG, GD), pp. 292–300.
RecSys-2011-GeXTL #collaboration: Collaborative filtering with collective training (YG, HX, AT, QL), pp. 281–284.
CIKM-2010-GeXZOYL #detection #evolution #named: Top-Eye: top-k evolving trajectory outlier detection (YG, HX, ZHZ, HTO, JY, KCL), pp. 1733–1736.
CIKM-2010-LiuCXD #collaboration #personalisation #ranking: Exploiting user interests for collaborative filtering: interests expansion via personalized ranking (QL, EC, HX, CHQD), pp. 1697–1700.
CIKM-2010-ZhuangLSHXSX #classification #collaboration #mining #multi: Collaborative Dual-PLSA: mining distinction and commonality across multiple domains for text classification (FZ, PL, ZS, QH, YX, ZS, HX), pp. 359–368.
KDD-2010-GeXTXGP #energy #mobile #recommendation: An energy-efficient mobile recommender system (YG, HX, AT, KX, MG, MJP), pp. 899–908.
CIKM-2009-CaoCYX #recommendation: Enhancing recommender systems under volatile userinterest drifts (HC, EC, JY, HX), pp. 1257–1266.
CIKM-2009-QianLLXSS #community #development #topic #what: What’s behind topic formation and development: a perspective of community core groups (TQ, QL, BL, HX, JS, PCYS), pp. 1843–1846.
KDD-2009-GeXZSGW #learning #multi: Multi-focal learning and its application to customer service support (YG, HX, WZ, RKS, XG, WW), pp. 349–358.
KDD-2009-WuXC #adaptation #clustering #metric: Adapting the right measures for K-means clustering (JW, HX, JC), pp. 877–886.
CIKM-2008-LuoZHXH #learning #multi: Transfer learning from multiple source domains via consensus regularization (PL, FZ, HX, YX, QH), pp. 103–112.
KDD-2008-WuXC #clustering #incremental #learning #named: SAIL: summation-based incremental learning for information-theoretic clustering (JW, HX, JC), pp. 740–748.
KDD-2008-ZhouX #correlation #perspective: Volatile correlation computation: a checkpoint view (WZ, HX), pp. 848–856.
SIGIR-2008-HuXZSL #clique #clustering #documentation #perspective: Hypergraph partitioning for document clustering: a unified clique perspective (TH, HX, WZ, SYS, HL), pp. 871–872.
SIGIR-2008-QuanCLX #adaptation #scalability #semantics: Adaptive label-driven scaling for latent semantic indexing (XQ, EC, QL, HX), pp. 827–828.
KDD-2007-GaoESCX #consistency #data mining #mining #problem #set: The minimum consistent subset cover problem and its applications in data mining (BJG, ME, JyC, OS, HX), pp. 310–319.
KDD-2007-LuoXLS #classification #distributed #network #peer-to-peer: Distributed classification in peer-to-peer networks (PL, HX, KL, ZS), pp. 968–976.
KDD-2007-TangWXZ #clustering #perspective: Enhancing semi-supervised clustering: a feature projection perspective (WT, HX, SZ, JW), pp. 707–716.
KDD-2007-WuWCX #analysis #composition: Local decomposition for rare class analysis (JW, HX, PW, JC), pp. 814–823.
CIKM-2006-QianXWC #adaptation #categorisation: Adapting association patterns for text categorization: weaknesses and enhancements (TQ, HX, YW, EC), pp. 782–783.
KDD-2006-XiongWC #clustering #metric #perspective #validation: K-means clustering versus validation measures: a data distribution perspective (HX, JW, JC), pp. 779–784.
CIKM-2005-XiongSK #database #learning #multi #privacy: Privacy leakage in multi-relational databases via pattern based semi-supervised learning (HX, MS, VK), pp. 355–356.
KDD-2004-SteinbachTXK: Generalizing the notion of support (MS, PNT, HX, VK), pp. 689–694.
KDD-2004-XiongSTK #bound #correlation #identification: Exploiting a support-based upper bound of Pearson’s correlation coefficient for efficiently identifying strongly correlated pairs (HX, SS, PNT, VK), pp. 334–343.
KDD-2004-YePLJXK #algorithm #composition #incremental #named #reduction: IDR/QR: an incremental dimension reduction algorithm via QR decomposition (JY, QL, HX, HP, RJ, VK), pp. 364–373.
SAC-2003-HuangXSP #mining: Mining Confident Colocation Rules without A Support Threshold (YH, HX, SS, JP), pp. 497–501.