Intelligent Database Systems Lab

國立雲林科技大學National Yunlin University of Science and Technology

Correlating burst events on streaming stock market data

Presenter : Shu-Ya Li

Authors : Michail Vlachos, Kun-Lung Wu,

Shyh-Kwei Chen, Philip S. Yu

DMKD, 2008

2Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Outline

Motivation

Objective

Methodology

Burst detection

Index structure

Experiments and Results

Conclusion

Personal Comments

3Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Motivation

People need to make decisions about financial.

‘Burstiness’ suggests more events of importance are happening within the same time frame.

The identification of bursts can provide useful insights about an imminent change in the monitoring quantity.

4Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Objectives

The effective burst detection. to do the right thing.

The efficient memory-based index. to do the thing right.

5Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology - Overview

Burst detection Index structure

BD q∩b

Q = {q1, . . . ql}

Bs = {b1, . . . , bk}

6Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Before Methodology …

Assuming a Gaussian data distribution τ=μ+3σ

ττ

Outliers, Noise…

150cm<身高 <170cm

身高 >200cm

7Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology - Burst detection

If si > τ, then time i is marked as a burst.

In this work we use an exponential model to describe the shape of the distribution

τ

τ

τ

x

Burst

假設 μ=10

P = 0.0004 x = 78.24P = 0.9 x = 1.05

8Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.

Building a CEI-Overlap index Burst intervals → Containment-encoded-intervals (CEI’s)

Insert a burst interval

Methodology - Index structure

9Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Methodology - Index structure

Identification of overlapping burst regions

10Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Experiments

Meaningfulness of results

11Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Experiments

The B+ tree insertion time is linear to the number of objects, while the CEI-index exhibits constant insertion time.

12Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Experiments

13Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Conclusion

We have presented a complete framework for efficient correlation of bursts.

The effectiveness of our scheme is attributed to the effective burst detection

the efficient memory-based index.

14Intelligent Database Systems Lab

N.Y.U.S.T.

I. M.Personal Comments

Advantage Many examples

Drawback …

Application Outlier detection