BibSLEIGH — Christos

Travelled to:

1 × Chile
1 × Egypt
1 × Germany
1 × Greece
1 × India
1 × Ireland
1 × Korea
1 × Norway
1 × Sweden
1 × Switzerland
1 × United Kingdom
2 × Australia
2 × Italy
2 × Spain
3 × France
31 × USA
5 × China
6 × Canada

Collaborated with:

H.Tong ∅ Y.Sakurai J.Leskovec I.Kamel J.Sun S.Papadimitriou L.Li L.Akoglu B.A.Prakash A.J.M.Traina C.T.Jr. J.Pan T.K.Sellis U.Kang T.Eliassi-Rad Y.Matsubara S.Kim H.V.Jagadish F.Korn D.Koutra N.Roussopoulos B.Gallagher D.H.Chau C.R.Palmer A.Beutel F.Guo D.Chakrabarti L.Wu E.P.Xing J.I.Hong R.T.Ng S.Christodoulakis S.Günnemann E.E.Papalexakis C.Böhm C.Plant Y.Tao D.Papadias E.Riedel J.Ha M.Yoshikawa M.McGlohon N.Sidiropoulos A.Metwally A.Kittur R.F.Murphy E.Airoldi B.Yi G.Proietti V.Gaede K.Lin A.Belussi D.N.Metaxas S.Roseman R.Chan A.Tomkins J.Vreeken S.Park P.S.Yu G.R.Ganger M.Faloutsos K.Henderson A.J.M.Traina N.Günnemann J.C.Tseng H.K.Pao C.Liu K.Onuma Y.Koren T.G.Kolda D.Tao E.Hoke J.M.Kleinberg K.S.McCurley A.Brockwell P.B.Gibbons Z.Bi D.Margaritis S.Thrun Y.Ishikawa R.Subramanya G.A.Gibson Y.Matias A.Silberschatz M.Ranganathan Y.Manolopoulos R.Agrawal R.Srikant W.Gatterbauer D.Jin Y.Ning W.G.v.Panhuis R.Rosenfeld A.Harpale D.Bae S.Hwang M.Jang K.Kim J.H.Lee H.Qu H.Jamjoom N.Du B.Wang J.McCann N.S.Pollard C.E.Tsourakakis G.L.Miller Z.Guo Z.Zhang E.P.M.d.Sousa D.S.Modha H.Yang P.Duygulu B.Liu R.F.S.Filho B.Seeger D.Nagle K.P.Sycara T.R.Payne A.Labrinidis Y.Kotidis A.F.Costa Y.Yamaguchi N.Shah T.Zou M.Jiang P.Cui S.Yang S.Kwon T.Iwata C.Lin S.Bay M.G.Anderle D.M.Steier N.Valler D.Andersen H.L.Razente M.C.N.Barioni W.Fu T.C.Mowry M.R.Vieira A.S.Arantes A.G.R.Balan J.F.R.Jr. O.Raz R.B.Buchheit M.Shaw P.Koopman E.L.Siegel Z.Protopapas D.Jensen A.Fyshe N.D.Sidiropoulos P.P.Talukdar T.M.Mitchell B.Fu J.Lin N.M.Sadeh I.Shafer K.Ren V.N.Boddeti Y.Abe M.Mongiovì P.Bogdanov R.Ranca A.K.Singh R.L.F.Cordeiro J.López C.M.Liang J.Liu S.Nath A.Terzis D.Surian N.Liu D.Lo E.Lim M.Seshadri S.Machiraju A.Sridharan J.Bolot A.Krause C.Guestrin J.M.VanBriesen N.S.Glance R.J.B.Jr. J.Kiernan R.Rantzau R.Kumar A.Tuzhilin G.Kossinets K.Maruhashi D.Tsichritzis P.Economopoulos A.Lee D.Lee J.Vandenbroeck C.C.Woo S.Basu M.J.Carey S.P.Ghosh M.A.W.Houtsma T.Imielinski B.R.Iyer A.Mahboob H.Miranda A.N.Swami T.E.Senator H.G.Goldberg A.Memory W.T.Young B.Rees R.Pierce D.Huang M.Reardon D.A.Bader E.Chow I.A.Essa J.Jones V.Bettadapura O.Green O.Kaya A.Zakrzewska E.Briscoe R.L.M.IV R.McColl L.Weiss T.G.Dietterich A.Fern W.Wong S.Das A.Emmott J.Irvine J.Y.Lee D.D.Corkill L.Friedland A.Gentzel

Talks about:

mine (40) graph (32) larg (22) data (21) fast (20) time (17) use (15) queri (11) network (10) databas (10)

Person: Christos Faloutsos

DBLP: Faloutsos:Christos

Facilitated 2 volumes:

Contributed to:

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

1998

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1991

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1986

1985

1983

2001

Wrote 138 papers:

KDD-2015-BeutelAF #behaviour #detection #graph #modelling #predict: Graph-Based User Behavior Modeling: From Prediction to Fraud Detection (AB, LA, CF), pp. 2309–2310.
KDD-2015-CostaYTTF #mining #modelling #named #process #social #social media: RSC: Mining and Modeling Temporal Activity in Social Media (AFC, YY, AJMT, CTJ, CF), pp. 269–278.
KDD-2015-ShahKZGF #graph #named #summary: TimeCrunch: Interpretable Dynamic Graph Summarization (NS, DK, TZ, BG, CF), pp. 1055–1064.
SIGMOD-2015-SakuraiMF #mining: Mining and Forecasting of Big Time-series Data (YS, YM, CF), pp. 919–922.
VLDB-2015-GatterbauerGKF: Linearized and Single-Pass Belief Propagation (WG, SG, DK, CF), pp. 581–592.
VLDB-2015-KoutraJNF #graph #interactive #mining #named #scalability #visualisation: Perseus: An Interactive Large-Scale Graph Mining and Visualization Tool (DK, DJ, YN, CF), pp. 1924–1935.
KDD-2014-GunnemannGF #detection #evolution #probability #rating #robust: Detecting anomalies in dynamic rating data: a robust probabilistic model for rating evolution (SG, NG, CF), pp. 841–850.
KDD-2014-JiangCBFY #behaviour #graph #named #scalability: CatchSync: catching synchronized behavior in large directed graphs (MJ, PC, AB, CF, SY), pp. 941–950.
KDD-2014-MatsubaraSPF #automation #mining #named: FUNNEL: automatic mining of spatially coevolving epidemics (YM, YS, WGvP, CF), pp. 105–114.
KDD-2014-PapalexakisFSTMF #algorithm #challenge #multi: Good-enough brain model: challenges, algorithms and discoveries in multi-subject experiments (EEP, AF, NDS, PPT, TMM, CF), pp. 95–104.
SIGMOD-2014-MatsubaraSF #automation #co-evolution #mining #named #sequence: AutoPlait: automatic mining of co-evolving time sequences (YM, YS, CF), pp. 193–204.
KDD-2013-FuLLFHS #feedback #mobile #people #why: Why people hate your app: making sense of user feedback in a mobile app store (BF, JL, LL, CF, JIH, NMS), pp. 1276–1284.
KDD-2013-SenatorGMYRPHRBCEJBCGKZBMMWDFWDEILKFCFGJ #database #detection #process: Detecting insider threats in a real corporate database of computer usage activity (TES, HGG, AM, WTY, BR, RP, DH, MR, DAB, EC, IAE, JJ, VB, DHC, OG, OK, AZ, EB, RLMI, RM, LW, TGD, AF, WKW, SD, AE, JI, JYL, DK, CF, DDC, LF, AG, DJ), pp. 1393–1401.
CIKM-2012-AkogluTVF #category theory #detection #performance #reliability: Fast and reliable anomaly detection in categorical data (LA, HT, JV, CF), pp. 415–424.
CIKM-2012-HaKKFP #recommendation: Top-N recommendation through belief propagation (JH, SHK, SWK, CF, SP), pp. 2343–2346.
CIKM-2012-TongPEFF #graph #scalability: Gelling, and melting, large graphs by edge manipulation (HT, BAP, TER, MF, CF), pp. 245–254.
KDD-2012-BeutelPRF #network #question: Interacting viruses in networks: can both survive? (AB, BAP, RR, CF), pp. 426–434.
KDD-2012-ChauAVTF #graph #interactive #named #scalability #visualisation: TourViz: interactive visualization of connection pathways in large graphs (DHC, LA, JV, HT, CF), pp. 1516–1519.
KDD-2012-HendersonGETBAKFL #graph #mining #named #scalability: RolX: structural role extraction & mining in large graphs (KH, BG, TER, HT, SB, LA, DK, CF, LL), pp. 1231–1239.
KDD-2012-KangPHF #algorithm #analysis #named #scalability: GigaTensor: scaling tensor analysis up by 100 times — algorithms and discoveries (UK, EEP, AH, CF), pp. 316–324.
KDD-2012-MatsubaraSFIY #mining #performance: Fast mining and forecasting of complex time-stamped events (YM, YS, CF, TI, MY), pp. 271–279.
KDD-2012-MatsubaraSPLF #information management: Rise and fall patterns of information diffusion: model and implications (YM, YS, BAP, LL, CF), pp. 6–14.
KDD-2012-ShaferRBAGF #approach #mining #monitoring #named: RainMon: an integrated approach to mining bursty timeseries monitoring data (IS, KR, VNB, YA, GRG, CF), pp. 1158–1166.
SIGMOD-2012-AkogluCKKF #graph #mining #named #scalability #visualisation: OPAvion: mining and visualization in large graphs (LA, DHC, UK, DK, CF), pp. 717–720.
SIGMOD-2012-FaloutsosK #algorithm #graph #mining #scalability: Managing and mining large graphs: patterns and algorithms (CF, UK), pp. 585–588.
SIGMOD-2012-MongioviBRSPF #mining #named #network: SigSpot: mining significant anomalous regions from time-evolving networks (MM, PB, RR, AKS, EEP, CF), p. 865.
VLDB-2012-MetwallyF #framework #multi #named #pipes and filters #scalability #similarity: V-SMART-Join: A Scalable MapReduce Framework for All-Pair Similarity Joins of Multisets and Vectors (AM, CF), pp. 704–715.
VLDB-2012-PrakashF #comprehension #graph #scalability: Understanding and Managing Cascades on Large Graphs (BAP, CF), pp. 2024–2025.
CHI-2011-ChauKHF #interactive #machine learning #named #network #scalability: Apolo: making sense of large network data by combining rich user interaction and machine learning (DHC, AK, JIH, CF), pp. 167–176.
CIKM-2011-BaeHKF: Constructing seminal paper genealogy (DHB, SMH, SWK, CF), pp. 2101–2104.
CIKM-2011-JangKFP #approximate #distance #linear: A linear-time approximation of the earth mover’s distance (MHJ, SWK, CF, SP), pp. 505–514.
CIKM-2011-KimKFL #analysis: Spectral analysis of a blogosphere (SWK, KNK, CF, JHL), pp. 2145–2148.
KDD-2011-ChauKHF #graph #interactive #machine learning #named #scalability #visualisation: Apolo: interactive large graph sensemaking by combining machine learning and visualization (DHC, AK, JIH, CF), pp. 739–742.
KDD-2011-CordeiroTTLKF #clustering #dataset #multi #pipes and filters #scalability: Clustering very large multi-dimensional datasets with MapReduce (RLFC, CTJ, AJMT, JL, UK, CF), pp. 690–698.
KDD-2011-HendersonGLAETF #graph #mining #recursion #using: It’s who you know: graph mining using recursive structural features (KH, BG, LL, LA, TER, HT, CF), pp. 663–671.
KDD-2011-KangTSLF #graph #named #scalability: GBASE: a scalable and general graph management system (UK, HT, JS, CYL, CF), pp. 1091–1099.
KDD-2011-LiLLNTF #cyber-physical #named: ThermoCast: a cyber-physical forecasting model for datacenters (LL, CJML, JL, SN, AT, CF), pp. 1370–1378.
SIGIR-2011-KimFH #information management: BlogCast effect on information diffusion in a blogosphere (SWK, CF, JH), pp. 1149–1150.
WCRE-2011-SurianLLTLF #collaboration #developer #network #people #recommendation: Recommending People in Developers’ Collaboration Network (DS, NL, DL, HT, EPL, CF), pp. 379–388.
KDD-2010-HendersonEFALMPT #approach #forensics #graph #metric #mining #multi: Metric forensics: a multi-level approach for mining volatile graphs (KH, TER, CF, LA, LL, KM, BAP, HT), pp. 163–172.
KDIR-2010-TsengPF #classification #markov #using: The Typhoon Track Classification using Tri-plots and Markov Chain (JCHT, HKKP, CF), pp. 364–369.
VLDB-2010-LiPF #linear: Parsimonious Linear Fingerprinting for Time Series (LL, BAP, CF), pp. 385–396.
CIKM-2009-TongQJF #graph #interactive #named #performance #proximity #query: iPoG: fast interactive proximity querying on graphs (HT, HQ, HJ, CF), pp. 1673–1676.
KDD-2009-DuFWA #communication #generative #network #scalability: Large human communication networks: patterns and a utility-driven generator (ND, CF, BW, LA), pp. 269–278.
KDD-2009-LiMPF #mining #named #sequence #summary: DynaMMo: mining and summarization of coevolving sequences with missing values (LL, JM, NSP, CF), pp. 507–516.
KDD-2009-LiuGF #named: BBM: bayesian browsing model from petabyte-scale data (CL, FG, CF), pp. 537–546.
KDD-2009-McGlohonBASF #detection #graph #named: SNARE: a link analytic system for graph labeling and risk detection (MM, SB, MGA, DMS, CF), pp. 1265–1274.
KDD-2009-OnumaTF #algorithm #named #novel #recommendation: TANGENT: a novel, “Surprise me”, recommendation algorithm (KO, HT, CF), pp. 657–666.
KDD-2009-PrakashVAFF #internet #named: BGP-lens: patterns and anomalies in internet routing updates (BAP, NV, DA, MF, CF), pp. 1315–1324.
KDD-2009-TsourakakisKMF #graph #named: DOULION: counting triangles in massive graphs with a coin (CET, UK, GLM, CF), pp. 837–846.
CIKM-2008-RazenteBTFT #approach #data access #metric #novel #optimisation #process #query #similarity: A novel optimization approach to efficiently process aggregate similarity queries in metric access methods (HLR, MCNB, AJMT, CF, CTJ), pp. 193–202.
CIKM-2008-TongSEF #mining #performance: Fast mining of complex time-stamped events (HT, YS, TER, CF), pp. 759–768.
KDD-2008-GallagherTEF #classification #network #using: Using ghost edges for classification in sparsely labeled networks (BG, HT, TER, CF), pp. 256–264.
KDD-2008-KumarTFJKLT #network #social: Social networks: looking ahead (RK, AT, CF, DJ, GK, JL, AT), p. 1060.
KDD-2008-LiFGMF #learning #linear #named #parallel #performance: Cut-and-stitch: efficient parallel learning of linear dynamical systems on smps (LL, WF, FG, TCM, CF), pp. 471–479.
KDD-2008-McGlohonAF #component #generative #graph: Weighted graphs and disconnected components: patterns and a generator (MM, LA, CF), pp. 524–532.
KDD-2008-SeshadriMSBFL #graph #mobile: Mobile call graphs: beyond power-law and lognormal distributions (MS, SM, AS, JB, CF, JL), pp. 596–604.
KDD-2008-TongPSYF #graph #mining #named #performance #scalability: Colibri: fast mining of large static and dynamic graphs (HT, SP, JS, PSY, CF), pp. 686–694.
SIGMOD-2008-BohmFP #clustering #component #independence #using: Outlier-robust clustering using independent components (CB, CF, CP), pp. 185–198.
VLDB-2008-GuoLFX #database #multi #named #query: C-DEM: a multi-modal query system for Drosophila Embryo databases (FG, LL, CF, EPX), pp. 1508–1511.
ICML-2007-LeskovecF #graph #modelling #multi #scalability #using: Scalable modeling of real graphs using Kronecker multiplication (JL, CF), pp. 497–504.
KDD-2007-GuoZXF #data mining #database #learning #mining #multimodal: Enhanced max margin learning on multimodal data mining in a multimedia database (ZG, ZZ, EPX, CF), pp. 340–349.
KDD-2007-LeskovecKGFVG #detection #effectiveness #network: Cost-effective outbreak detection in networks (JL, AK, CG, CF, JMV, NSG), pp. 420–429.
KDD-2007-SunFPY #graph #mining #named #scalability: GraphScope: parameter-free mining of large time-evolving graphs (JS, CF, SP, PSY), pp. 687–696.
KDD-2007-TongFGE #graph #pattern matching #performance #scalability: Fast best-effort pattern matching in large attributed graphs (HT, CF, BG, TER), pp. 737–746.
KDD-2007-TongFK #graph #mining #performance #proximity: Fast direction-aware proximity for graph mining (HT, CF, YK), pp. 747–756.
SIGMOD-2007-FaloutsosKS #graph #matrix #mining #scalability #tool support #using: Mining large graphs and streams using matrix and tensor tools (CF, TGK, JS), p. 1174.
CIKM-2006-TrainaTVAF #performance #query #similarity: Efficient processing of complex similarity queries in RDBMS through query rewriting (CTJ, AJMT, MRV, ASA, CF), pp. 4–13.
KDD-2006-BohmFPP #clustering #robust: Robust information-theoretic clustering (CB, CF, JYP, CP), pp. 65–75.
KDD-2006-LeskovecF #graph #scalability: Sampling from large graphs (JL, CF), pp. 631–636.
KDD-2006-PanGBXTF #automation #image #mining: Automatic mining of fruit fly embryo images (JYP, AGRB, EPX, AJMT, CF), pp. 693–698.
KDD-2006-SunTF #analysis #graph: Beyond streams and graphs: dynamic tensor analysis (JS, DT, CF), pp. 374–383.
KDD-2006-TongF #performance #problem: Center-piece subgraphs: problem definition and fast solutions (HT, CF), pp. 404–413.
SAC-2006-SousaTTF #data type #evolution: Evaluating the intrinsic dimension of evolving data streams (EPMdS, AJMT, CTJ, CF), pp. 643–648.
VLDB-2006-HokeSF #clustering #monitoring #named #scalability: InteMon: Intelligent System Monitoring on Large Clusters (EH, JS, CF), pp. 1239–1242.
VLDB-2006-RodriguesTTFL #graph #interactive #mining #named #scalability #visualisation: GMine: A System for Scalable, Interactive Graph Visualization and Mining (JFRJ, HT, AJMT, CF, JL), pp. 1195–1198.
KDD-2005-LeskovecKF #graph: Graphs over time: densification laws, shrinking diameters and possible explanations (JL, JMK, CF), pp. 177–187.
PODS-2005-SakuraiYF #distance #named #performance #similarity: FTW: fast similarity search under the time warping distance (YS, MY, CF), pp. 326–337.
SIGMOD-2005-MurphyF #database #image #research: Research issues in protein location image databases (RFM, CF), pp. 966–967.
SIGMOD-2005-SakuraiPF #correlation #mining #named: BRAID: Stream Mining through Group Lag Correlations (YS, SP, CF), pp. 599–610.
VLDB-2005-PapadimitriouSF #multi #streaming: Streaming Pattern Discovery in Multiple Time-Series (SP, JS, CF), pp. 697–708.
KDD-2004-AiroldiF #network: Recovering latent time-series from their observed sums: network tomography with particle filters (EA, CF), pp. 30–39.
KDD-2004-ChakrabartiPMF #automation: Fully automatic cross-associations (DC, SP, DSM, CF), pp. 79–88.
KDD-2004-FaloutsosMT #performance: Fast discovery of connection subgraphs (CF, KSM, AT), pp. 118–127.
KDD-2004-PanYFD #automation #correlation #multi: Automatic multimedia cross-modal correlation discovery (JYP, HJY, CF, PD), pp. 653–658.
SEKE-2004-RazBSKF #automation #elicitation: Automated Assistance for Eliciting User Expectations (OR, RBB, MS, PK, CF), pp. 80–85.
SIGMOD-2004-Faloutsos #mining: Indexing and Mining Streams (CF), p. 969.
SIGMOD-2004-TaoFPL #predict: Prediction and Indexing of Moving Objects with Unknown Motion Patterns (YT, CF, DP, BL), pp. 611–622.
VLDB-2004-AgrawalBFKRS #database: Auditing Compliance with a Hippocratic Database (RA, RJBJ, CF, JK, RR, RS), pp. 516–527.
CIKM-2003-TaoFP #estimation #multi #query: The power-method: a comprehensive estimation technique for multi-dimensional queries (YT, CF, DP), pp. 83–90.
VLDB-2003-PapadimitriouBF #adaptation #mining: Adaptive, Hands-Off Stream Mining (SP, AB, CF), pp. 560–571.
CIKM-2002-ChakrabartiF #automation #named #scalability #using: F4: large-scale automated forecasting using fractals (DC, CF), pp. 2–9.
CIKM-2002-Faloutsos #data mining #mining #network #self: Future directions in data mining: streams, networks, self-similarity and power laws (CF), p. 93.
CIKM-2002-PanF #data mining #library #mining #quote #video: “GeoPlot”: spatial data mining on video libraries (JYP, CF), pp. 405–412.
CIKM-2002-TrainaTFF #data access #how #metric: How to improve the pruning ability of dynamic metric access methods (CTJ, AJMT, RFSF, CF), pp. 219–226.
KDD-2002-PalmerGF #data mining #graph #mining #named #performance #scalability: ANF: a fast and scalable tool for data mining in massive graphs (CRP, PBG, CF), pp. 81–90.
KDD-2002-WuF #performance #scalability: Making every bit count: fast nonlinear axis scaling (LW, CF), pp. 664–669.
VLDB-2002-Faloutsos #analysis #data mining #mining #similarity: Sensor Data Mining: Similarity Search and Pattern Analysis (CF).
KDD-2001-BiFK #mining: The “DGX” distribution for mining massive, skewed data (ZB, CF, FK), pp. 17–26.
KDD-2001-TrainaTPF #data mining #mining #multi #named #scalability #tool support: Tri-plots: scalable tools for multidimensional data mining (AJMT, CTJ, SP, CF), pp. 184–193.
VLDB-2001-MargaritisFT #data mining #mining #named #performance #scalability: NetCube: A Scalable Tool for Fast Data Mining and Compression (DM, CF, ST), pp. 311–320.
SIGMOD-2000-FaloutsosSTT #using: Spatial Join Selectivity Using Power Laws (CF, BS, AJMT, CTJ), pp. 177–188.
SIGMOD-2000-PalmerF #clustering #data mining #mining: Density Biased Sampling: An Improved Method for Data Mining and Clustering (CRP, CF), pp. 82–92.
SIGMOD-2000-RiedelFGN #data mining #for free #mining: Data Mining on an OLTP System (Nearly) for Free (ER, CF, GRG, DN), pp. 13–21.
VLDB-2000-WuFSP #adaptation #feedback #named #retrieval: FALCON: Feedback Adaptive Loop for Content-Based Retrieval (LW, CF, KPS, TRP), pp. 297–306.
VLDB-2000-YiF #performance #sequence: Fast Time Sequence Indexing for Arbitrary Lp Norms (BKY, CF), pp. 385–394.
CIKM-1998-ProviettiF #estimation #query: Selectivity Estimation of Window Queries (GP, CF), pp. 340–347.
VLDB-1998-IshikawaSF #database #multi #named #query: MindReader: Querying Databases Through Multiple Examples (YI, RS, CF), pp. 218–227.
VLDB-1998-KornLKF #data mining #mining #paradigm #performance: Ratio Rules: A New Paradigm for Fast, Quantifiable Data Mining (FK, AL, YK, CF), pp. 582–593.
VLDB-1998-RiedelGF #data mining #mining #multi #scalability: Active Storage for Large-Scale Data Mining and Multimedia (ER, GAG, CF), pp. 62–73.
SIGMOD-1997-KornJF #ad hoc #dataset #query #scalability #sequence: Efficiently Supporting Ad Hoc Queries in Large Datasets of Time Sequences (FK, HVJ, CF), pp. 289–300.
VLDB-1997-FaloutsosJS #summary: Recovering Information from Summary Data (CF, HVJ, NS), pp. 36–45.
VLDB-1997-SellisRF #data access #multi: Multidimensional Access Methods: Trees Have Grown Everywhere (TKS, NR, CF), pp. 13–14.
VLDB-1996-FaloutsosG #analysis #using: Analysis of n-Dimensional Quadtrees using the Hausdorff Fractal Dimension (CF, VG), pp. 40–50.
VLDB-1996-FaloutsosMS #modelling #multi #using: Modeling Skewed Distribution Using Multifractals and the “80-20” Law (CF, YM, AS), pp. 307–317.
VLDB-1996-KornSFSP #database #image #nearest neighbour #performance: Fast Nearest Neighbor Search in Medical Image Databases (FK, NS, CF, ELS, ZP), pp. 215–226.
SIGMOD-1995-Faloutsos #database #multi: Indexing Multimedia Databases (CF), p. 467.
SIGMOD-1995-FaloutsosL #algorithm #dataset #multi #named #performance #visualisation: FastMap: A Fast Algorithm for Indexing, Data-Mining and Visualization of Traditional and Multimedia Datasets (CF, KIL), pp. 163–174.
VLDB-1995-BelussiF #correlation #query #using: Estimating the Selectivity of Spatial Queries Using the “Correlation” Fractal Dimension (AB, CF), pp. 299–310.
PODS-1994-FaloutsosK #analysis #concept #independence #using: Beyond Uniformity and Independence: Analysis of R-trees Using the Concept of Fractal Dimension (CF, IK), pp. 4–13.
SIGMOD-1994-AgrawalCFGHIIMMSS #database #mining #named: Quest: A Project on Database Mining (RA, MJC, CF, SPG, MAWH, TI, BRI, AM, HM, RS, ANS), p. 514.
SIGMOD-1994-FaloutsosRM #database #performance #sequence: Fast Subsequence Matching in Time-Series Databases (CF, MR, YM), pp. 419–429.
VLDB-1994-KamelF #using: Hilbert R-tree: An Improved R-tree using Fractals (IK, CF), pp. 500–509.
CIKM-1993-KamelF #on the: On Packing R-trees (IK, CF), pp. 490–499.
SIGMOD-1992-KamelF #parallel: Parallel R-trees (IK, CF), pp. 195–204.
VLDB-1992-FaloutsosJ #on the: On B-Tree Indices for Skewed Distributions (CF, HVJ), pp. 363–374.
SIGMOD-1991-NgFS #flexibility: Flexible Buffer Allocation Based on Marginal Gains (RTN, CF, TKS), pp. 387–396.
VLDB-1991-FaloutsosNS #flexibility #predict: Predictive Load Control for Flexible Buffer Allocation (CF, RTN, TKS), pp. 265–274.
PODS-1989-FaloutsosM #clustering #fault #using: Declustering Using Error Correcting Codes (CF, DNM), pp. 253–258.
PODS-1989-FaloutsosR #retrieval: Fractals for Secondary Key Retrieval (CF, SR), pp. 247–252.
VLDB-1988-FaloutsosC #comparison #data access #design #performance #scalability: Fast Text Access Methods for Optical and Large Magnetic Disks: Designs and Performance Comparison (CF, RC), pp. 280–293.
SIGMOD-1987-FaloutsosSR #analysis #data access #object-oriented: Analysis of Object Oriented Spatial Access Methods (CF, TKS, NR), pp. 426–439.
VLDB-1987-SellisRF #multi: The R+-Tree: A Dynamic Index for Multi-Dimensional Objects (TKS, NR, CF), pp. 507–518.
SIGMOD-1986-Faloutsos #multi #using: Multiattribute Hashing Using Gray Codes (CF), pp. 227–238.
SIGMOD-1985-Faloutsos #comparison #design #performance: Signature files: Design and Performance Comparison of Some Signature Extraction Methods (CF), pp. 63–82.
VLDB-1985-FaloutsosC #design #query: Design of a Signature File Method that Accounts for Non-Uniform Occurrence and Query Frequencies (CF, SC), pp. 165–170.
VLDB-1983-TsichritzisCEFLLVW #multi: A Multimedia Office Filing System (DT, SC, PE, CF, AL, DL, JV, CCW), pp. 2–7.
JCDL-2001-PanFV #classification #mining #named #video: VideoGraph: a new tool for video mining and classification (JYP, CF), pp. 116–117.