correlating burst events on streaming stock market data

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


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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.


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I. M.Objectives

The effective burst detection. to do the right thing.

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


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I. M.Methodology - Overview

Burst detection Index structure

BD q∩b

Q = {q1, . . . ql}

Bs = {b1, . . . , bk}


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I. M.Before Methodology …

Assuming a Gaussian data distribution τ=μ+3σ

ττ

Outliers, Noise…

150cm<身高 <170cm

身高 >200cm


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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


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I. M.

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

Insert a burst interval

Methodology - Index structure


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I. M.Methodology - Index structure

Identification of overlapping burst regions


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I. M.Experiments

Meaningfulness of results


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I. M.Experiments

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


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I. M.Experiments


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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.


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I. M.Personal Comments

Advantage Many examples

Drawback …

Application Outlier detection

correlating burst events on streaming stock market data

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