jagadish powerpoint

  • data mining: concepts and techniques — chapter 8 — 8.2 mining ...

    Moon, K. Whang, W. Loh. Duality Based Subsequence Matching in Time-Series Databases, ICDE’02 B.-K. Yi, H. V. Jagadish, and C. Faloutsos. Efficient retrieval of …


    Added: 6 year ago

  • spatial indexing

    ... Implementations FL (Fixed Length) FD (Fixed length-Depth) VL (Variable length) Use a B+-tree to index the z-values and answer range queries References H. V. Jagadish ...

    lect7 05.ppt

    Added: 6 year ago

  • multi-modal biometrics for one billion people

    Enrollment to AuthenticationClient and Station OverviewUIDAI. Sanjay Jain. Jagadish. Agenda. Overview. Aaadhaar Enrollment Station – Sneak Preview. Unveiling the …


    Added: 6 year ago

  • pattern matching with acceleration data

    2) F. Korn, H. V. Jagadish, and C. Faloutsos. Efficiently supporting ad hoc queries in large datasets of time sequences. In SIGMOD 1997 . 3) K. pong Chan and A. W.-C. …


    Added: 6 year ago

  • aom 2010 会议征稿通知

    Chennupati JAGADISH, Australia National Univ, AUS. Arthur E. T. CHIOU, Yang-Ming University, Taiwan. Fengzhou Fang, Tianjin University, China

    AOM2010 Call for papers updated choy.ppt

    Added: 6 year ago

  • queries and data models for prediction and measurement in remos

    Sub ? surName=jagadish)) Query returns each entry that satisfies objectClass=orgUnit and has at least one child entry that satisfies surName=jagadish.


    Added: 6 year ago

  • references (1)

    [JKM98] H. V. Jagadish, N. Koudas, S. Muthukrishnan, V. Poosala, K. Sevcik, and T. Suel. “Optimal Histograms with Quality Guarantees”. VLDB 1998.

    approxQP references.ppt

    Added: 6 year ago