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Bloom Filter � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � , � � � � � � � � � � � � � � � � � � � � � � � � � �

by unknown authors
"... [11,12] � � � � � � � � � � � � � � � � [13] � � � � � � � � [14] � � � � � � � � � � [7−9]. � � � �,Bloom Filter � � Hash � � � � � � � � � � � � � � � � � � � � � � ..."
Abstract - Add to MetaCart
[11,12] � � � � � � � � � � � � � � � � [13] � � � � � � � � [14] � � � � � � � � � � [7−9]. � � � �,Bloom Filter � � Hash � � � � � � � � � � � � � � � � � � � � � �

Compressed Bloom Filters

by Michael Mitzenmacher , 2001
"... A Bloom filter is a simple space-efficient randomized data structure for representing a set in order to support membership queries. Although Bloom filters allow false positives, for many applications the space savings outweigh this drawback when the probability of an error is sufficiently low. We in ..."
Abstract - Cited by 257 (10 self) - Add to MetaCart
A Bloom filter is a simple space-efficient randomized data structure for representing a set in order to support membership queries. Although Bloom filters allow false positives, for many applications the space savings outweigh this drawback when the probability of an error is sufficiently low. We

Network Applications of Bloom Filters: A Survey

by Andrei Broder, Michael Mitzenmacher - Internet Mathematics , 2002
"... Abstract. ABloomfilter is a simple space-efficient randomized data structure for representing a set in order to support membership queries. Bloom filters allow false positives but the space savings often outweigh this drawback when the probability of an error is controlled. Bloom filters have been u ..."
Abstract - Cited by 513 (16 self) - Add to MetaCart
Abstract. ABloomfilter is a simple space-efficient randomized data structure for representing a set in order to support membership queries. Bloom filters allow false positives but the space savings often outweigh this drawback when the probability of an error is controlled. Bloom filters have been

On bloom filters

by Odysseas Papapetrou, Wolf Siberski, Wolfgang Nejdl , 2006
"... Bloom filters are heavily used in the literature for efficiently representing sets with elements from a large universe. However, the current literature lacks some important functionality on bloom filters which can be proven useful in several application domains, especially in distributed and P2P sys ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
Bloom filters are heavily used in the literature for efficiently representing sets with elements from a large universe. However, the current literature lacks some important functionality on bloom filters which can be proven useful in several application domains, especially in distributed and P2P

Bloom Filter Query Algorithm

by Xie Kun, Wen Ji-gang, Zhang Da-fang, Xie Gao-gang
"... Abstract: This paper surveys the mathematics behind Bloom filters, some important variations and network-related applications of Bloom filters. The current researches show that although Bloom filters start drawing significant attention from the academic community and there has been considerable pro ..."
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Abstract: This paper surveys the mathematics behind Bloom filters, some important variations and network-related applications of Bloom filters. The current researches show that although Bloom filters start drawing significant attention from the academic community and there has been considerable

Weighted Bloom Filter

by Jehoshua Bruck, et al.
"... A Bloom filter is a simple randomized data structure that answers membership query with no false negative and a small false positive probability. It is an elegant data compression technique for membership information and has broad applications. In this paper, we generalize the traditional Bloom fi ..."
Abstract - Cited by 6 (0 self) - Add to MetaCart
A Bloom filter is a simple randomized data structure that answers membership query with no false negative and a small false positive probability. It is an elegant data compression technique for membership information and has broad applications. In this paper, we generalize the traditional Bloom

The Dynamic Bloom Filters

by Deke Guo, Jie Wu, Honghui Chen, Ye Yuan, Xueshan Luo - In Proc. IEEE Infocom , 2006
"... Abstract—A Bloom filter is an effective, space-efficient data structure for concisely representing a set and supporting approximate membership queries. Traditionally, the Bloom filter and its variants just focus on how to represent a static set and decrease the false positive probability to a suffic ..."
Abstract - Cited by 25 (3 self) - Add to MetaCart
Abstract—A Bloom filter is an effective, space-efficient data structure for concisely representing a set and supporting approximate membership queries. Traditionally, the Bloom filter and its variants just focus on how to represent a static set and decrease the false positive probability to a

Weighted Bloom Filter

by unknown authors
"... Abstract—A Bloom filter is a simple randomized data structure that answers membership query with no false negative and a small false positive probability. It is an elegant data compression technique for membership information and has broad applica-tions. In this paper, we generalize the traditional ..."
Abstract - Add to MetaCart
Abstract—A Bloom filter is a simple randomized data structure that answers membership query with no false negative and a small false positive probability. It is an elegant data compression technique for membership information and has broad applica-tions. In this paper, we generalize the traditional

Adaptive Bloom Filter

by unknown authors
"... Abstract — A Bloom filter is a simple randomized data structure that answers membership query with no false negative and a small false positive probability. It is an elegant data compression technique for membership information, and has broad applications. In this paper, we generalize the traditiona ..."
Abstract - Add to MetaCart
Abstract — A Bloom filter is a simple randomized data structure that answers membership query with no false negative and a small false positive probability. It is an elegant data compression technique for membership information, and has broad applications. In this paper, we generalize

Scalable Bloom Filters

by Paulo Sérgio Almeida Carlos Baquero, David Hutchison, Nuno Preguiça
"... Bloom Filters provide space-efficient storage of sets at the cost of a probability of false positives on mem-bership queries. The size of the filter must be defined a priori based on the number of elements to store and the desired false positive probability, being impossible to store extra elements ..."
Abstract - Cited by 25 (1 self) - Add to MetaCart
Bloom Filters provide space-efficient storage of sets at the cost of a probability of false positives on mem-bership queries. The size of the filter must be defined a priori based on the number of elements to store and the desired false positive probability, being impossible to store extra elements
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