BibSLEIGH — Min

Travelled to:

1 × Australia
1 × Chile
1 × Ireland
1 × Portugal
1 × Singapore
1 × South Africa
2 × France
3 × China
4 × USA

Collaborated with:

S.Ma Y.Liu Y.Zhang K.Zhang L.Ru Y.Wang X.Ye K.Wang K.Zhou Y.Zhang A.Cui J.Nie Y.Choi K.Ogata C.Wang S.Huo C.Wang Z.Liu H.Zhang Y.Fu R.Xiang G.Lai Q.Xing C.Wei R.Cen B.Zhou Y.Chen J.Tang J.Sun X.Zhu M.Zheng J.Qian L.Yang D.Hou M.Kan T.Sakai Z.Dou T.Yamamoto M.P.Kato R.Song M.Iwata

Talks about:

model (7) base (6) search (5) user (5) sentiment (4) click (4) web (4) result (3) level (3) framework (2)

Person: Min Zhang

DBLP: Zhang:Min

Contributed to:

2015

2014

2013

2012

2010

2009

2008

2007

2000

Wrote 22 papers:

SIGIR-2015-LiuCTS0MZ #predict: Different Users, Different Opinions: Predicting Search Satisfaction with Mouse Movement Information (YL, YC, JT, JS, MZ, SM, XZ), pp. 493–502.
SIGIR-2015-LiuLZ0M #web: Influence of Vertical Result in Web Search Examination (ZL, YL, KZ, MZ, SM), pp. 193–202.
CIKM-2014-Huo0LM #performance #query: Improving Tail Query Performance by Fusion Model (SH, MZ, YL, SM), pp. 559–568.
CIKM-2014-LiuWZNZM #web: From Skimming to Reading: A Two-stage Examination Model for Web Search (YL, CW, KZ, JYN, MZ, SM), pp. 849–858.
CIKM-2014-ZhangZZLM #comprehension #constraints #matrix: Understanding the Sparsity: Augmented Matrix Factorization with Sampled Constraints on Unobservables (YZ, MZ, YZ, YL, SM), pp. 1189–1198.
SIGIR-2014-ZhangL0ZLM #analysis #modelling #recommendation #sentiment: Explicit factor models for explainable recommendation based on phrase-level sentiment analysis (YZ, GL, MZ, YZ, YL, SM), pp. 83–92.
SIGIR-2014-ZhangZ0LM #classification #overview #sentiment: Do users rate or review?: boost phrase-level sentiment labeling with review-level sentiment classification (YZ, HZ, MZ, YL, SM), pp. 1027–1030.
WRLA-2014-ZhangCO #framework #semantics #standard #𝕂: A Formal Semantics of the OSEK/VDX Standard in 𝕂 Framework and Its Applications (MZ, YC, KO), pp. 280–296.
CIKM-2013-XingLNZMZ #modelling: Incorporating user preferences into click models (QX, YL, JYN, MZ, SM, KZ), pp. 1301–1310.
HT-2013-ZhangZLM #collaboration #framework #matrix: A general collaborative filtering framework based on matrix bordered block diagonal forms (YZ, MZ, YL, SM), pp. 219–224.
SIGIR-2013-SakaiDYLZKSI #mining #summary #topic: Summary of the NTCIR-10 INTENT-2 task: subtopic mining and search result diversification (TS, ZD, TY, YL, MZ, MPK, RS, MI), pp. 761–764.
SIGIR-2013-WangLZMZQZ #modelling: Incorporating vertical results into search click models (CW, YL, MZ, SM, MZ, JQ, KZ), pp. 503–512.
SIGIR-2013-ZhangZLM #collaboration #matrix: Improve collaborative filtering through bordered block diagonal form matrices (YZ, MZ, YL, SM), pp. 313–322.
CIKM-2012-CuiZLMZ #twitter: Discover breaking events with popular hashtags in twitter (AC, MZ, YL, SM, KZ), pp. 1794–1798.
SIGIR-2012-WeiLZMRZ #novel #web: Fighting against web spam: a novel propagation method based on click-through data (CW, YL, MZ, SM, LR, KZ), pp. 395–404.
TPDL-2012-CuiYHKLZM #named #web: PrEV: Preservation Explorer and Vault for Web 2.0 User-Generated Content (AC, LY, DH, MYK, YL, MZ, SM), pp. 101–112.
ICSE-2010-WangZ #case study #development #multi #policy: Penalty policies in professional software development practice: a multi-method field study (YW, MZ), pp. 39–47.
CIKM-2009-CenLZZRM: Exploring relevance for clicks (RC, YL, MZ, BZ, LR, SM), pp. 1847–1850.
CIKM-2008-WangZRM #automation #online #ranking #topic #using: Automatic online news topic ranking using media focus and user attention based on aging theory (CW, MZ, LR, SM), pp. 1033–1042.
SIGIR-2008-ZhangY #generative #retrieval #sentiment #topic: A generation model to unify topic relevance and lexicon-based sentiment for opinion retrieval (MZ, XY), pp. 411–418.
CIKM-2007-FuXLZM #formal method: A CDD-based formal model for expert finding (YF, RX, YL, MZ, SM), pp. 881–884.
TOOLS-ASIA-2000-ZhangW #design pattern #implementation #object-oriented #undo #using: Implementing Undo/Redo in PDF Studio Using Object-Oriented Design Pattern (MZ, KW), pp. 58–64.