BibSLEIGH — Mohammed_Javeed

Travelled to:

1 × Canada
16 × USA

Collaborated with:

∅ W.Li S.Parthasarathy M.Ogihara K.Sequeira C.C.Aggarwal N.Lesh N.Ramakrishnan L.Zhao K.Gouda H.Yildirim V.Chaoji G.Ramesh W.Maniatty M.Cierniak M.Peters I.Assent T.Seidl B.K.Szymanski C.D.Carothers S.Dwarkadas N.Ta J.Wang J.Feng A.Veloso W.M.Jr. M.Cristo M.A.Gonçalves F.Pan G.Cong A.K.H.Tung J.Yang G.Piatetsky-Shapiro R.Grossman C.Djeraba R.Feldman L.Getoor

Talks about:

mine (15) data (6) sequenc (5) cluster (4) associ (4) algorithm (3) effect (3) rule (3) structur (2) frequent (2)

Person: Mohammed Javeed Zaki

DBLP: Zaki:Mohammed_Javeed

Facilitated 1 volumes:

Contributed to:

2010

2007

2006

2005

2003

2002

2000

1999

1998

1997

1996

1995

Wrote 24 papers:

VLDB-2010-YildirimCZ #graph #named #reachability #scalability: GRAIL: Scalable Reachability Index for Large Graphs (HY, VC, MJZ), pp. 276–284.
KDD-2007-AggarwalTWFZ #clustering #documentation #framework #named #xml: Xproj: a framework for projected structural clustering of xml documents (CCA, NT, JW, JF, MJZ), pp. 46–55.
CIKM-2006-VelosoMCGZ #classification #documentation #lazy evaluation #multi: Multi-evidence, multi-criteria, lazy associative document classification (AV, WMJ, MC, MAG, MJZ), pp. 218–227.
KDD-2006-Piatetsky-ShapiroGDFGZ #challenge #data mining #mining #question: Is there a grand challenge or X-prize for data mining? (GPS, RG, CD, RF, LG, MJZ), pp. 954–956.
KDD-2005-ZakiPAS #algorithm #category theory #clustering #dataset #effectiveness #mining #named: CLICKS: an effective algorithm for mining subspace clusters in categorical datasets (MJZ, MP, IA, TS), pp. 736–742.
KDD-2005-ZakiR #mining #reasoning #set #using: Reasoning about sets using redescription mining (MJZ, NR), pp. 364–373.
SIGMOD-2005-ZhaoZ #3d #algorithm #array #clustering #effectiveness #mining #named: TriCluster: An Effective Algorithm for Mining Coherent Clusters in 3D Microarray Data (LZ, MJZ), pp. 694–705.
KDD-2003-PanCTYZ #biology #dataset #named: Carpenter: finding closed patterns in long biological datasets (FP, GC, AKHT, JY, MJZ), pp. 637–642.
KDD-2003-SequeiraZSC #data mining #locality #mining #source code: Improving spatial locality of programs via data mining (KS, MJZ, BKS, CDC), pp. 649–654.
KDD-2003-ZakiA #classification #effectiveness #named #xml: XRules: an effective structural classifier for XML data (MJZ, CCA), pp. 316–325.
KDD-2003-ZakiG #mining #performance #using: Fast vertical mining using diffsets (MJZ, KG), pp. 326–335.
PODS-2003-RameshMZ #data mining #mining #theory and practice: Feasible itemset distributions in data mining: theory and application (GR, WM, MJZ), pp. 284–295.
KDD-2002-SequeiraZ #data mining #mining #named: ADMIT: anomaly-based data mining for intrusions (KS, MJZ), pp. 386–395.
KDD-2002-Zaki #mining: Efficiently mining frequent trees in a forest (MJZ), pp. 71–80.
CIKM-2000-Zaki #category theory #constraints #mining #sequence: Sequence Mining in Categorical Domains: Incorporating Constraints (MJZ), pp. 422–429.
KDD-2000-Zaki #generative: Generating non-redundant association rules (MJZ), pp. 34–43.
CIKM-1999-ParthasarathyZOD #incremental #interactive #mining #sequence: Incremental and Interactive Sequence Mining (SP, MJZ, MO, SD), pp. 251–258.
KDD-1999-LeshZO #classification #mining #sequence: Mining Features for Sequence Classification (NL, MJZ, MO), pp. 342–346.
CIKM-1998-Zaki #performance #sequence: Efficient Enumeration of Frequent Sequences (MJZ), pp. 68–75.
KDD-1998-ParthasarathyZL #memory management #mining #parallel: Memory Placement Techniques for Parallel Association Mining (SP, MJZ, WL), pp. 304–308.
KDD-1998-ZakiLO #mining #named #sequence: PlanMine: Sequence Mining for Plan Failures (MJZ, NL, MO), pp. 369–374.
KDD-1997-ZakiPOL #algorithm #performance: New Algorithms for Fast Discovery of Association Rules (MJZ, SP, MO, WL), pp. 283–286.
HPDC-1996-ZakiLP #network: Customized Dynamic Load Balancing for a Network of Workstations (MJZ, WL, SP), pp. 282–291.
HPDC-1995-CierniakLZ #scheduling: Loop Scheduling for Heterogeneity (MC, WL, MJZ), pp. 78–85.