BibSLEIGH — Martin

Travelled to:

1 × Austria
1 × France
1 × Norway
1 × Spain
1 × United Kingdom
16 × USA
2 × China
4 × Canada

Collaborated with:

H.Kriegel M.Jamali S.Moghaddam X.Xu W.Jin J.Sander R.Ge M.Schubert I.Davidson M.Ankerst R.Frank ∅ B.Hu G.Melli M.A.Tayebi U.Glässer B.J.Gao J.Blomo M.Field T.Huang A.J.Knobbe S.S.Ravi F.Moser F.Beil P.L.Brantingham J.Habibi C.Li A.K.H.Tung O.L.Griffith S.J.M.Jones J.Pei Y.Tao Z.Hu K.Yu C.Elsen A.Frommelt J.Cai O.Schulte H.Xiong M.Wimmer R.She F.Chen K.Wang J.L.Gardy F.S.L.Brinkman

Talks about:

recommend (9) cluster (9) base (9) spatial (7) trust (6) model (6) mine (6) databas (5) review (5) data (5)

Person: Martin Ester

DBLP: Ester:Martin

Facilitated 1 volumes:

Contributed to:

2014

2013

2012

2011

2010

2009

2007

2006

2005

2004

2003

2002

2001

2000

1999

1998

1997

1996

1995

Wrote 37 papers:

KDD-2014-TayebiEGB #embedded #learning #predict #using: Spatially embedded co-offence prediction using supervised learning (MAT, ME, UG, PLB), pp. 1789–1798.
RecSys-2013-BlomoEF #challenge: RecSys challenge 2013 (JB, ME, MF), pp. 489–490.
RecSys-2013-Ester #network #recommendation #social: Recommendation in social networks (ME), pp. 491–492.
RecSys-2013-HuE #modelling #online #recommendation #social #social media #topic: Spatial topic modeling in online social media for location recommendation (BH, ME), pp. 25–32.
CIKM-2012-MoghaddamE #design #mining #modelling #on the: On the design of LDA models for aspect-based opinion mining (SM, ME), pp. 803–812.
SIGIR-2012-MoghaddamE #mining: Aspect-based opinion mining from product reviews (SM, ME), p. 1184.
CIKM-2011-MoghaddamJE #online #overview #personalisation #predict #quality #recommendation: Review recommendation: personalized prediction of the quality of online reviews (SM, MJ, ME), pp. 2249–2252.
RecSys-2011-JamaliHE #network #probability #rating #recommendation #social: A generalized stochastic block model for recommendation in social rating networks (MJ, TH, ME), pp. 53–60.
RecSys-2011-TayebiJEGF #named #recommendation: CrimeWalker: a recommendation model for suspect investigation (MAT, MJ, ME, UG, RF), pp. 173–180.
SIGIR-2011-MoghaddamE #aspect-oriented #learning #named #online: ILDA: interdependent LDA model for learning latent aspects and their ratings from online product reviews (SM, ME), pp. 665–674.
CIKM-2010-MelliE #concept #identification #ontology: Supervised identification and linking of concept mentions to a domain-specific ontology (GM, ME), pp. 1717–1720.
CIKM-2010-MoghaddamE #mining: Opinion digger: an unsupervised opinion miner from unstructured product reviews (SM, ME), pp. 1825–1828.
RecSys-2010-JamaliE #matrix #network #recommendation #social #trust: A matrix factorization technique with trust propagation for recommendation in social networks (MJ, ME), pp. 135–142.
KDD-2009-FrankEK #approach #classification #multi: A multi-relational approach to spatial classification (RF, ME, AJK), pp. 309–318.
KDD-2009-JamaliE #named #random #recommendation #trust: TrustWalker: a random walk model for combining trust-based and item-based recommendation (MJ, ME), pp. 397–406.
RecSys-2009-JamaliE #network #recommendation #trust #using: Using a trust network to improve top-N recommendation (MJ, ME), pp. 181–188.
RecSys-2009-MoghaddamJEH #feedback #named #recommendation #trust #using: FeedbackTrust: using feedback effects in trust-based recommendation systems (SM, MJ, ME, JH), pp. 269–272.
KDD-2007-DavidsonRE #clustering #incremental #performance: Efficient incremental constrained clustering (ID, SSR, ME), pp. 240–249.
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-GeEJD #clustering #constraints: Constraint-driven clustering (RG, ME, WJ, ID), pp. 320–329.
KDD-2007-MoserGE #analysis #clustering #specification: Joint cluster analysis of attribute and relationship data withouta-priori specification of the number of clusters (FM, RG, ME), pp. 510–519.
VLDB-2007-LiTJE #on the: On Dominating Your Neighborhood Profitably (CL, AKHT, WJ, ME), pp. 818–829.
KDD-2006-GaoGEJ #clustering: Discovering significant OPSM subspace clusters in massive gene expression data (BJG, OLG, ME, SJMJ), pp. 922–928.
VLDB-2005-PeiJET #approach #semantics: Catching the Best Views of Skyline: A Semantic Approach Based on Decisive Subspaces (JP, WJ, ME, YT), pp. 253–264.
KDD-2004-EsterGJH #data mining #mining #problem #segmentation: A microeconomic data mining problem: customer-oriented catalog segmentation (ME, RG, WJ, ZH), pp. 557–562.
VLDB-2004-EsterKS #crawling #performance: Accurate and Efficient Crawling for Relevant Websites (ME, HPK, MS), pp. 396–407.
KDD-2003-SheCWEGB #predict: Frequent-subsequence-based prediction of outer membrane proteins (RS, FC, KW, ME, JLG, FSLB), pp. 436–445.
KDD-2002-BeilEX #clustering: Frequent term-based text clustering (FB, ME, XX), pp. 436–442.
KDD-2002-EsterKS #mining #web: Web site mining: a new way to spot competitors, customers and suppliers in the world wide web (ME, HPK, MS), pp. 249–258.
CIKM-2001-YuXEK #collaboration #performance: Selecting Relevant Instances for Efficient and Accurate Collaborative Filtering (KY, XX, ME, HPK), pp. 239–246.
KDD-2000-AnkerstEK #classification #effectiveness #towards: Towards an effective cooperation of the user and the computer for classification (MA, ME, HPK), pp. 179–188.
KDD-1999-AnkerstEEK #approach #classification #interactive #visual notation: Visual Classification: An Interactive Approach to Decision Tree Construction (MA, CE, ME, HPK), pp. 392–396.
KDD-1998-EsterFKS #algorithm #database #detection: Algorithms for Characterization and Trend Detection in Spatial Databases (ME, AF, HPK, JS), pp. 44–50.
VLDB-1998-EsterKSWX #clustering #incremental #mining: Incremental Clustering for Mining in a Data Warehousing Environment (ME, HPK, JS, MW, XX), pp. 323–333.
KDD-1997-EsterKSX #database #detection #set: Density-Connected Sets and their Application for Trend Detection in Spatial Databases (ME, HPK, JS, XX), pp. 10–15.
KDD-1996-EsterKSX #algorithm #clustering #database #scalability: A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise (ME, HPK, JS, XX), pp. 226–231.
KDD-1995-EsterKX #clustering #database #interface #scalability: A Database Interface for Clustering in Large Spatial Databases (ME, HPK, XX), pp. 94–99.