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Results 1 - 10
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451
An improved data stream summary: The Count-Min sketch and its applications
- J. Algorithms
, 2004
"... Abstract. We introduce a new sublinear space data structure—the Count-Min Sketch — for summarizing data streams. Our sketch allows fundamental queries in data stream summarization such as point, range, and inner product queries to be approximately answered very quickly; in addition, it can be applie ..."
Abstract
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Cited by 413 (43 self)
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Abstract. We introduce a new sublinear space data structure—the Count-Min Sketch — for summarizing data streams. Our sketch allows fundamental queries in data stream summarization such as point, range, and inner product queries to be approximately answered very quickly; in addition, it can
Approximate aggregation techniques for sensor databases
- In ICDE
, 2004
"... In the emerging area of sensor-based systems, a significant challenge is to develop scalable, fault-tolerant methods to extract useful information from the data the sensors collect. An approach to this data management problem is the use of sensor database systems, exemplified by TinyDB and Cougar, w ..."
Abstract
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Cited by 301 (6 self)
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is not possible in general. With this in mind, we investigate the use of approximate in-network aggregation using small sketches. Our contributions are as follows: 1) we generalize well known duplicateinsensitive sketches for approximating COUNT to handle SUM (and by extension, AVG and other aggregates), 2) we
Surfing wavelets on streams: One-pass summaries for approximate aggregate queries
- In VLDB
, 2001
"... Abstract We present techniques for computing small spacerepresentations of massive data streams. These are inspired by traditional wavelet-based approx-imations that consist of specific linear projections of the underlying data. We present general"sketch " based methods for capturi ..."
Abstract
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Cited by 215 (16 self)
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Abstract We present techniques for computing small spacerepresentations of massive data streams. These are inspired by traditional wavelet-based approx-imations that consist of specific linear projections of the underlying data. We present general"sketch " based methods
Approximate query
"... Abstract The in–network aggregation paradigm in sensor networks provides a versatile approach for evaluating aggregate queries. Traditional approaches need a separate aggregate to be computed and communicated for each query and hence do not scale well with the number of queries. Since approximate qu ..."
Abstract
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the number of sensors that report values in a given range. We construct summary data–structures called linear sketches, over the sensor data using in–network aggregation and use them to answer aggregate queries in an approximate manner at the base–station. There is a trade–off between accuracy of the query
Analysis of a very large AltaVista query log
, 1998
"... In this paper we present an analysis of a 280 GB AltaVista Search Engine query log consisting of approximately 1 billion entries for search requests over a period of six weeks. This represents approximately 285 million user sessions, each an attempt to fill a single information need. We present an a ..."
Abstract
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Cited by 195 (2 self)
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In this paper we present an analysis of a 280 GB AltaVista Search Engine query log consisting of approximately 1 billion entries for search requests over a period of six weeks. This represents approximately 285 million user sessions, each an attempt to fill a single information need. We present
Sketching streams through the net: Distributed approximate query tracking
- In VLDB
, 2005
"... While traditional database systems optimize for performance on one-shot query processing, emerging large-scale monitoring applications require continuous tracking of complex dataanalysis queries over collections of physically-distributed streams. Thus, effective solutions have to be simultaneously s ..."
Abstract
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Cited by 78 (20 self)
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nutshell, our algorithms rely on tracking general-purpose randomized sketch summaries of local streams at remote sites along with concise prediction models of local site behavior in order to produce highly communication- and space/time-efficient solutions. The end result is a powerful approximate query
Sketch techniques for approximate query processing
- Synposes for Approximate Query Processing: Samples, Histograms, Wavelets and Sketches, Foundations and Trends in Databases. NOW publishers
, 2011
"... sample ..."
Estimating the Selectivity of Spatial Queries Using the `Correlation' Fractal Dimension
, 1995
"... We examine the estimation of selectivities for range and spatial join queries in real spatial databases. As we have shown earlier [FK94a], real point sets: (a) violate consistently the "uniformity" and "independence" assumptions, (b) can often be described as "fractals" ..."
Abstract
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Cited by 125 (18 self)
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We examine the estimation of selectivities for range and spatial join queries in real spatial databases. As we have shown earlier [FK94a], real point sets: (a) violate consistently the "uniformity" and "independence" assumptions, (b) can often be described as "
Private queries in location based services: anonymizers are not necessary
- In SIGMOD
, 2008
"... Mobile devices equipped with positioning capabilities (e.g., GPS) can ask location-dependent queries to Location Based Services (LBS). To protect privacy, the user location must not be disclosed. Existing solutions utilize a trusted anonymizer between the users and the LBS. This approach has several ..."
Abstract
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Cited by 133 (16 self)
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work, our approach achieves stronger privacy for snapshots of user locations; moreover, it is the first to provide provable privacy guarantees against correlation attacks. We use our framework to implement approximate and exact algorithms for nearest-neighbor search. We optimize query execution
Approximate data collection in sensor networks using probabilistic models
- IN ICDE
, 2006
"... Wireless sensor networks are proving to be useful in a variety of settings. A core challenge in these networks is to minimize energy consumption. Prior database research has proposed to achieve this by pushing data-reducing operators like aggregation and selection down into the network. This approac ..."
Abstract
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Cited by 148 (7 self)
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. This approach has proven unpopular with early adopters of sensor network technology, who typically want to extract complete “dumps ” of the sensor readings, i.e., to run “SELECT *” queries. Unfortunately, because these queries do no data reduction, they consume significant energy in current sensornet query
Results 1 - 10
of
451
