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Travelled to:
1 × Australia
1 × Austria
1 × China
1 × Cyprus
1 × Germany
1 × Korea
1 × Spain
16 × USA
2 × France
3 × Canada
Collaborated with:
T.Lappas N.Koudas V.J.Tsotras G.Kollios G.Das M.Vlachos V.Kalogeraki C.Domeniconi P.Papapetrou G.Valkanas D.Zeinalipour-Yazti B.Arai D.Kotsakos V.Athitsos S.Subramaniam S.Guha D.Zhang M.R.Vieira H.Mannila E.J.Keogh A.Kotsifakos J.Hollmén T.Palpanas D.Srivastava S.Lin P.Sakkos E.Terzi N.Sarkas D.Tsirogiannis C.Meek Z.Vagena M.Hadjieleftheriou P.B.Chou E.Grossman P.Kamesam R.Agrawal J.Gehrke P.Raghavan R.Khardon H.Toivonen V.Hristidis M.Platakis M.Potamias D.Papadopoulos V.B.Zordan M.Cardle A.Markowetz B.Seeger D.Kotzias N.Kanhabua K.Nørvåg D.Agarwal D.Barman N.E.Young F.Korn
Talks about:
queri (8) effici (6) data (6) dimension (5) rang (5) approxim (4) search (4) bursti (4) aggreg (4) approach (3)

Person: Dimitrios Gunopulos

DBLP DBLP: Gunopulos:Dimitrios

Facilitated 1 volumes:

KDD 2006Ed

Contributed to:

SIGIR 20142014
CIKM 20132013
SIGMOD 20132013
VLDB 20132013
KDD 20122012
VLDB 20122012
VLDB 20112011
KDD 20102010
RecSys 20102010
VLDB 20102010
KDD 20092009
VLDB 20092009
SIGMOD 20082008
KDD 20072007
VLDB 20072007
CIKM 20062006
ICEIS ISAS 20062006
VLDB 20062006
KDD 20042004
SIGMOD 20042004
VLDB 20042004
KDD 20032003
VLDB 20032003
CIKM 20022002
KDD 20022002
PODS 20022002
ICML 20012001
PODS 20012001
KDD 20002000
SIGMOD 20002000
PODS 19991999
SIGMOD 19981998
PODS 19971997

Wrote 37 papers:

SIGIR-2014-KotsakosLKGKN #approach #documentation
A burstiness-aware approach for document dating (DK, TL, DK, DG, NK, KN), pp. 1003–1006.
CIKM-2013-ValkanasG #how #web
How the live web feels about events (GV, DG), pp. 639–648.
SIGMOD-2013-LappasVGT #mining #named #process
STEM: a spatio-temporal miner for bursty activity (TL, MRV, DG, VJT), pp. 1021–1024.
VLDB-2013-KotsakosSKG #health #monitoring #named #smarttech #using
SmartMonitor: Using Smart Devices to Perform Structural Health Monitoring (DK, PS, VK, DG), pp. 1282–1285.
KDD-2012-LappasVG #invariant #mining #performance
Efficient and domain-invariant competitor mining (TL, GV, DG), pp. 408–416.
VLDB-2012-KotsifakosPHGAK #named #sequence
Hum-a-song: A Subsequence Matching with Gaps-Range-Tolerances Query-By-Humming System (AK, PP, JH, DG, VA, GK), pp. 1930–1933.
VLDB-2012-LappasVGT #on the
On The Spatiotemporal Burstiness of Terms (TL, MRV, DG, VJT), pp. 836–847.
VLDB-2011-KotsifakosPHG #framework #sequence
A Subsequence Matching with Gaps-Range-Tolerances Framework: A Query-By-Humming Application (AK, PP, JH, DG), pp. 761–771.
KDD-2010-LappasTGM #network #social
Finding effectors in social networks (TL, ET, DG, HM), pp. 1059–1068.
RecSys-2010-LappasG #interactive #network #recommendation #social
Interactive recommendations in social endorsement networks (TL, DG), pp. 127–134.
VLDB-2010-AraiDGHK #approach #cost analysis #multi #retrieval
An Access Cost-Aware Approach for Object Retrieval over Multiple Sources (BA, GD, DG, VH, NK), pp. 1125–1136.
KDD-2009-LappasAPKG #documentation #on the #sequence
On burstiness-aware search for document sequences (TL, BA, MP, DK, DG), pp. 477–486.
VLDB-2009-PapapetrouAKG #database #scalability #sequence
Reference-Based Alignment in Large Sequence Databases (PP, VA, GK, DG), pp. 205–216.
SIGMOD-2008-AthitsosPPKG #approximate #sequence
Approximate embedding-based subsequence matching of time series (VA, PP, MP, GK, DG), pp. 365–378.
KDD-2007-AgarwalBGYKS #effectiveness #performance #summary
Efficient and effective explanation of change in hierarchical summaries (DA, DB, DG, NEY, FK, DS), pp. 6–15.
VLDB-2007-AraiDGK #algorithm #metric
Anytime Measures for Top-k Algorithms (BA, GD, DG, NK), pp. 914–925.
VLDB-2007-DasGKS #ad hoc #data type #query
Ad-hoc Top-k Query Answering for Data Streams (GD, DG, NK, NS), pp. 183–194.
CIKM-2006-Zeinalipour-YaztiLG #distributed #similarity
Distributed spatio-temporal similarity search (DZY, SL, DG), pp. 14–23.
ICEIS-ISAS-2006-SubramaniamKG #behaviour #evolution #predict #process
Business Processes: Behavior Prediction and Capturing Reasons for Evolution (SS, VK, DG), pp. 3–10.
VLDB-2006-DasGKT #query #using
Answering Top-k Queries Using Views (GD, DG, NK, DT), pp. 451–462.
VLDB-2006-SubramaniamPPKG #detection #modelling #online #parametricity #using
Online Outlier Detection in Sensor Data Using Non-Parametric Models (SS, TP, DP, VK, DG), pp. 187–198.
KDD-2004-VlachosGD #distance #invariant #metric
Rotation invariant distance measures for trajectories (MV, DG, GD), pp. 707–712.
SIGMOD-2004-VlachosMV #identification #online #query
Identifying Similarities, Periodicities and Bursts for Online Search Queries (MV, CM, ZV, DG), pp. 131–142.
VLDB-2004-PalpanasCGKZ #database #scalability
Indexing Large Human-Motion Databases (EJK, TP, VBZ, DG, MC), pp. 780–791.
KDD-2003-GuhaGK #correlation #data type
Correlating synchronous and asynchronous data streams (SG, DG, NK), pp. 529–534.
KDD-2003-VlachosHGK #distance #metric #multi
Indexing multi-dimensional time-series with support for multiple distance measures (MV, MH, DG, EJK), pp. 216–225.
VLDB-2003-KoudasGGSV #approximate #constraints #optimisation #parametricity #performance #query
Efficient Approximation Of Optimization Queries Under Parametric Aggregation Constraints (SG, DG, NK, DS, MV), pp. 778–789.
CIKM-2002-KalogerakiGZ #network #peer-to-peer
A local search mechanism for peer-to-peer networks (VK, DG, DZY), pp. 300–307.
KDD-2002-VlachosDGKK #classification #reduction #visualisation
Non-linear dimensionality reduction techniques for classification and visualization (MV, CD, DG, GK, NK), pp. 645–651.
PODS-2002-ZhangTG #performance
Efficient Aggregation over Objects with Extent (DZ, VJT, DG), pp. 121–132.
ICML-2001-DomeniconiG #approach #approximate #classification #dataset #multi #nearest neighbour #performance #query #scalability
An Efficient Approach for Approximating Multi-dimensional Range Queries and Nearest Neighbor Classification in Large Datasets (CD, DG), pp. 98–105.
PODS-2001-ZhangMTGS #performance
Efficient Computation of Temporal Aggregates with Range Predicates (DZ, AM, VJT, DG, BS).
KDD-2000-ChouGGK #identification
Identifying prospective customers (PBC, EG, DG, PK), pp. 447–456.
SIGMOD-2000-GunopulosKTD #approximate #multi #query
Approximating Multi-Dimensional Aggregate Range Queries over Real Attributes (DG, GK, VJT, CD), pp. 463–474.
PODS-1999-KolliosGT #mobile #on the
On Indexing Mobile Objects (GK, DG, VJT), pp. 261–272.
SIGMOD-1998-AgrawalGGR #automation #clustering #data mining #mining
Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications (RA, JG, DG, PR), pp. 94–105.
PODS-1997-GunopulosKMT #data mining #machine learning #mining
Data mining, Hypergraph Transversals, and Machine Learning (DG, RK, HM, HT), pp. 209–216.

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