Person: Dimitrios Gunopulos

DBLP: Gunopulos:Dimitrios

Facilitated 1 volumes:

Ed

Contributed to:

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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.