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Lossy Count Algorithm

The lossy count algorithm is an algorithm to identify elements in a data stream whose frequency count exceed a user-given threshold. The frequency… 
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Papers overview

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2015
2015
A Lossy Counting-Based State of Charge Estimation Method and Its Application to Electric Vehicles
Estimating the residual capacity or state-of-charge (SoC) of commercial batteries on-line without destroying them or interrupting… 
2015
2015
Cardinality Estimation in Shared-Nothing Parallel Data Flows
Shared nothing parallel dataflow systems aim to bridge the gap between MapReduce and RDBMSs by combining parallel execution of… 
2013
2013
Video traffic analysis for abnormal event detection using frequent item set mining
As powerful computers and cameras have become wide spread, the number of applications using vision techniques has increased… 
2011
2011
A load shedding scheme for frequent pattern mining in transactional data streams
In this paper, we study overload handling for frequent-pattern mining in online data streams. For a mining system with an e… 
2011
2011
A New Classification Algorithm for Data Stream
Associative classification (AC) which is based on association rules has shown great promise over many other classification… 
2010
2010
Associative Classification over Data Streams
Based on association rules, Associative classification (AC) has shown great promise over many other classification techniques on… 
2010
2010
An adaptive method for identifying heavy hitters combining sampling and data streaming counting
Identifying heavy hitters is essential for network monitoring, management, charging and etc. Existing methods in the literature… 
2008
2008
Improved Approximate Frequency Counts Algorithm based on "Lossy Counting"
2007
2007
State-of-the-art in data stream mining
2005
2005
Deterministic Sampling beyond EASE : Reducing Multi-Dimensional Data ∗
A wide range of mining and analysis problems involve extracting knowledge from count data. A general approach that scales well… 
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