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461,861
massive data sets
, 2015
"... Order statistics and estimating cardinalities of massive data sets ..."
Synopsis Data Structures for Massive Data Sets
"... Abstract. Massive data sets with terabytes of data are becoming commonplace. There is an increasing demand for algorithms and data structures that provide fast response times to queries on such data sets. In this paper, we describe a context for algorithmic work relevant to massive data sets and a f ..."
Abstract
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Cited by 116 (13 self)
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Abstract. Massive data sets with terabytes of data are becoming commonplace. There is an increasing demand for algorithms and data structures that provide fast response times to queries on such data sets. In this paper, we describe a context for algorithmic work relevant to massive data sets and a
SCOPE: Easy and Efficient Parallel Processing of Massive Data Sets
"... Companies providing cloud-scale services have an increasing need to store and analyze massive data sets such as search logs and click streams. For cost and performance reasons, processing is typically done on large clusters of shared-nothing commodity machines. It is imperative to develop a programm ..."
Abstract
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Cited by 206 (9 self)
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Companies providing cloud-scale services have an increasing need to store and analyze massive data sets such as search logs and click streams. For cost and performance reasons, processing is typically done on large clusters of shared-nothing commodity machines. It is imperative to develop a
Clustering in Massive Data Sets
- Handbook of massive data sets
, 1999
"... We review the time and storage costs of search and clustering algorithms. We exemplify these, based on case-studies in astronomy, information retrieval, visual user interfaces, chemical databases, and other areas. Sections 2 to 6 relate to nearest neighbor searching, an elemental form of clustering, ..."
Abstract
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Cited by 17 (0 self)
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, and a basis for clustering algorithms to follow. Sections 7 to 11 review a number of families of clustering algorithm. Sections 12 to 14 relate to visual or image representations of data sets, from which a number of interesting algorithmic developments arise.
Data Streams: Algorithms and Applications
, 2005
"... In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerg ..."
Abstract
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Cited by 532 (22 self)
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analysis, mining text message streams and processing massive data sets in general. Researchers in Theoretical Computer Science, Databases, IP Networking and Computer Systems are working on the data stream challenges. This article is an overview and survey of data stream algorithmics and is an updated
An Approach to mining massive Data
"... Modern internet applications, scientific applications have created a need to manage immense amounts of data quickly. According to a Study, the amount of information created and replicated is forecasted to reach 35 zettabytes (trillion gigabytes) by the end of this decade. The exponentially growing d ..."
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Modern internet applications, scientific applications have created a need to manage immense amounts of data quickly. According to a Study, the amount of information created and replicated is forecasted to reach 35 zettabytes (trillion gigabytes) by the end of this decade. The exponentially growing
Order Statistics and Estimating Cardinalities of massive Data Sets
, 2011
"... statistics and estimating cardinalities of massive data sets ..."
What Use is Statistics for Massive Data?
"... Statistics in the broad sense is about extracting information from data. The common view of statistics is much narrower, though. Often, it is seen only as a set of cookbook methods that are designed for small sets of data that are obtained according to a known design or sampling plan. The massive dy ..."
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Statistics in the broad sense is about extracting information from data. The common view of statistics is much narrower, though. Often, it is seen only as a set of cookbook methods that are designed for small sets of data that are obtained according to a known design or sampling plan. The massive
Data Mining: Concepts and Techniques
, 2000
"... Our capabilities of both generating and collecting data have been increasing rapidly in the last several decades. Contributing factors include the widespread use of bar codes for most commercial products, the computerization of many business, scientific and government transactions and managements, a ..."
Abstract
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Cited by 3156 (22 self)
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warehouses, and other massive information repositories. Data mining is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, neural networks, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information
Results 1 - 10
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