Abstract
The problem of estimating the kth frequency moment Fk over a data stream by looking at the items exactly once as they arrive was posed in . A succession of algorithms have been proposed for this problem . Recently, Indyk and Woodru have presented the rst algorithm for estimating Fk, for k > 2, using space O (n1 2=k), matching the space lower bound (up to poly-logarithmic factors) for this problem (n is the number of distinct items occurring in the stream.) In this paper, we presen ....etc

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Hello,

I am new here in this forum.
I am working on data streams anonymization.
I am currently on literature survey.
From literature, i discovered that the adult data set on the UCI repository is usually used to test data stream anonymization using k-anonymity.
Please how is the UCI data set which is static simulated as streaming data?
Also is there any form of free source code available on data streams anonymization.
Thank you. ....etc

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Hello,

Please can i get free source code on data streams annonymization?
Thank you.

Ade
[email protected] ....etc

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Abstract.
We consider the problem of estimating hybrid frequency moments of two dimensional data
streams. In this model, data is viewed to be organized in a matrix form (Ai;j)1 i;j; n. The entries
Ai;j are updated coordinate-wise, in arbitrary order and possibly multiple times. The updates include
both increments and decrements to the current value of Ai;j . The hybrid frequency moment Fp;q(A)
is de ned as
Pn
j=1 ....etc

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Abstract.
We present an algorithm for estimating entropy of data streams consisting of insertion and deletion operations using O(1) space.
1 1 Introduction
Recently, there has been an emergence of monitoring applications in diverse areas, including, network traf_c monitoring, network topology monitoring, sensor networks, _nancial market monitoring, web-log monitoring, etc.. In these applications, data is generated rapidly and continuously, and must be analyzed very ef_ciently, in realtime, to identify large trends, anomalies ....etc

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Abstract.
We present deterministic sub-linear space algorithms for a number of problems over update data streams, including, estimating fre- quencies of items and ranges, nding approximate frequent items and approximate -quantiles, estimating inner-products, constructing near- optimal B-bucket histograms and estimating entropy. We also present new lower bound results for several problems over update data streams.
1 Introduction
The data streaming model presents a computational model for a variety of monitoring appl ....etc

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Abstract.
We consider a basic problem in the general data streaming model, namely, to estimate
a vector f 2 Zn that is arbitrarily updated (i.e., incremented or decremented) coordinatewise.
The estimate f 2 Zn must satisfy k f fk1 _ _kfk1, that is, 8i ( fi fi _ _kfk1). It is
known to have O(_ 1) randomized space upper bound , (_ 1 log(_n)) space lower bound
and deterministic space upper bound of (_ 2) bits.1 We show that any deterministic
algorithm for this problem requires space (_ 2(logkfk1)) bits.
1 Introd ....etc

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Abstract.
The problem of estimating the kth frequency moment Fk, for any
non-negative integral value of k, over a data stream by looking at the items exactly
once as they arrive, was considered in a seminal paper by Alon, Matias and
Szegedy . They present a sampling based algorithm to estimate Fk where,
k 2, using space O(n1 1/k)). Coppersmith and Kumar and , using
different methods, present algorithms for estimating Fk with space complexity
O
(n1 1/(k 1)). In this paper, we present an algorithm for estimati ....etc

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myself sharath and we are working on nymble project, we are not getting data flow diagram for this project so can anyone please send the data flow diagram to my email address i.e [email protected] or [email protected]. thanking you, Sharath ....etc

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Abstract.
We present a randomized procedure named Hierarchical Sampling from Sketches (HSS) that can be used for estimating a class of functions over the frequency vector f of update streams of the form (S) = Pn i=1 ( fi ).We illustrate this by applying the HSS technique to design nearly space-optimal algorithms for estimating the pth moment of the frequency vector, for real p _ 2 and for estimating the entropy of a data stream. 3
1 Introduction
A variety of applications in diverse areas, such as, networking, database syst ....etc

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