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Title: uml diagram for online intrusion alert aggregation with generative data stream modeling
Page Link: uml diagram for online intrusion alert aggregation with generative data stream modeling -
Posted By:
Created at: Thursday 04th of October 2012 03:05:32 PM
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Title: online intrusion alert aggregation with generative data stream modeling pdf
Page Link: online intrusion alert aggregation with generative data stream modeling pdf -
Posted By:
Created at: Thursday 15th of March 2012 12:07:05 AM
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Title: Automotive Stream Based Data Management
Page Link: Automotive Stream Based Data Management -
Posted By: Computer Science Clay
Created at: Friday 07th of August 2009 07:59:53 PM
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An embedded system is a special-purpose system in which the computer is completely encapsulated by the device it controls. Unlike a general-purpose computer, such as a personal computer, an embedded system performs one or a few pre-defined tasks, usually with very specific requirements. Since the system is dedicated to specific tasks, design engineers can optimize it, reducing the size and cost of the product.

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Title: Distributing Frequency-Dependent Data Stream Computations
Page Link: Distributing Frequency-Dependent Data Stream Computations -
Posted By: smart paper boy
Created at: Friday 12th of August 2011 12:35:06 PM
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Abstract
Data stream computations in domains such as internet applications are often performed in a highly distributed fashion in order to save time. An example is the class of applications that use the Google Mapreduce framework of scalable distributed processing as presented by (Dean & Ghemawat 2004). A basic question here is: what kind of data stream computations admit scalable and efficient distributed algorithms? We show that the class of data stream computations that approximate functions of the frequency vector of the stream ca ....etc

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Title: Data stream algorithms via expander graphs
Page Link: Data stream algorithms via expander graphs -
Posted By: smart paper boy
Created at: Friday 12th of August 2011 01:08:57 PM
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Abstract.
We present a simple way of designing deterministic algorithms for problems in the data stream model via lossless expander graphs.We illustrate this by considering two problems, namely, k-sparsity testing and estimating frequency of items.
1 Introduction
We say that an n-dimensional vector f from Zn is k-sparse if it has at most k non-zero entries. The problem is to test whether f is k-sparse or no after it has been subject to a sequence of coordinate wise updates in arbitrary order, that is, f is the frequency vec ....etc

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Title: Online mining maximal frequent itemsets over the data stream
Page Link: Online mining maximal frequent itemsets over the data stream -
Posted By: seminar class
Created at: Monday 28th of March 2011 07:03:26 PM
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DESCRIPTION:
A data stream is a massive, open-ended sequence of data elements continuously generated at a rapid rate. Mining data streams is more difficult than mining static databases because the huge, high-speed and continuous characteristics of streaming data. In this paper, we propose a new one-pass algorithm called DSM-MFI (stands for Data Stream Mining for Maximal Frequent Itemsets), which mines the set of all maximal frequent itemsets in landmark windows over data streams.
The proposed algorithm DSM-MFI ....etc

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Title: future enhancement for online intrusion alert aggregation with generative data stream modeling pdf
Page Link: future enhancement for online intrusion alert aggregation with generative data stream modeling pdf -
Posted By:
Created at: Thursday 04th of October 2012 02:22:33 AM
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Title: Aurora A New Model And Architecture For Data Stream Management
Page Link: Aurora A New Model And Architecture For Data Stream Management -
Posted By: summer project pal
Created at: Sunday 23rd of January 2011 11:37:03 PM
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Aurora: A New Model And Architecture For Data Stream Management
B.Tech Seminar Report
by
Shafeek T K
Department of Computer Science And Engineering
Government Engineering College, Thrissur
December 2010



Abstract
This paper introduces a new class of application called monitoring applications, These
applications show di er substantially from conventional data processing. The fact that
a software system should process and react to, inputs in continuous manner f ....etc

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Title: Deterministically estimating data stream frequencies
Page Link: Deterministically estimating data stream frequencies -
Posted By: smart paper boy
Created at: Friday 12th of August 2011 02:13:21 PM
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Abstract.
We consider updates to an n-dimensional frequency vector of a data stream, that is, the vector f is updated coordinate-wise by means of insertions or deletions in any arbitrary order. A fundamental problem in this model is to recall the vector approximately, that is to return an estimate ^ f of f such that j ^ fi ....etc

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Title: Application of Stream Data Time-Series Pattern Reliance Mining in Stock Market Analys
Page Link: Application of Stream Data Time-Series Pattern Reliance Mining in Stock Market Analys -
Posted By: project topics
Created at: Thursday 22nd of April 2010 02:27:15 AM
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The Application of Stream Data Time-Series Pattern Reliance Mining in Stock Market Analysis

With the rapid development of computer information technology, a new data model-the stream data emerged. The stream data is coming continuously, quickly, changing with time, and may be unpredictable and unlimited in the way. The emergence of stream data has brought new challenges from the nature ofthe data applied to static database technology and data mining technology. At present, the stream data has been widely used in telecommunications, financial ....etc

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