1) Counting Bloom Filter(CBF)
计数型Bloom过滤器
1.
This paper compares and analyzes the similarities and differences among Counting Bloom Filter(CBF), Spectral Bloom Filter(SBF) and Dynamic Counting Filter(DCF), gives some examples and applications in data stream which include duplicate items detecting and frequent items mining.
该文分析比较计数型Bloom过滤器、光谱Bloom过滤器和动态计数过滤器的异同点及适用场合,介绍Bloom过滤器在重复项检测及频繁项挖掘中的应用,总结Bloom过滤器给数据流带来的挑战,包括元素突发问题及数据流相异元素数目变化问题。
2) Bloom filter
Bloom过滤器
1.
A novel method is proposed which utilizes Bloom filter to construct a space-efficient service group filter.
在分析现有相关研究的基础上,提出了基于Bloom过滤器的网格服务发现机制。
2.
This paper introduces Bloom filter into Growth Codes algorithm to reduce the redundant data exchange.
针对此问题,通过在Growth Codes算法中引入Bloom过滤器减少冗余数据传输。
3.
After analyzing the search performance of the Hash algorithm for the mass URIs, this paper puts forward an improved algorithm based on Bloom filter.
该文在分析现有Hash算法对海量URI查找的性能后,提出一种基于Bloom过滤器的改进算法。
3) counting Bloom filter
计数型bloom filter
1.
In each of the multi-rules sets,which is divided by tuple space,different shared-node counting Bloom filter bits groups are created.
针对此问题,设计了一种新的过滤器方案,该方案在网络设备驱动层采用节点共享计数型bloom filter技术,通过改进哈希函数的集合,减少了位数组元素的碰撞率,实现了过滤规则的动态添加和删除。
4) Spectral Bloom Filter(SBF)
光谱Bloom过滤器
1.
This paper compares and analyzes the similarities and differences among Counting Bloom Filter(CBF), Spectral Bloom Filter(SBF) and Dynamic Counting Filter(DCF), gives some examples and applications in data stream which include duplicate items detecting and frequent items mining.
该文分析比较计数型Bloom过滤器、光谱Bloom过滤器和动态计数过滤器的异同点及适用场合,介绍Bloom过滤器在重复项检测及频繁项挖掘中的应用,总结Bloom过滤器给数据流带来的挑战,包括元素突发问题及数据流相异元素数目变化问题。
5) Bloom filter
Bloom滤波器
1.
IP source address spoofing filtering based on Bloom filter
基于Bloom滤波器的IP源地址假冒过滤
6) Dynamic Counting Filter(DCF)
动态计数过滤器
1.
This paper compares and analyzes the similarities and differences among Counting Bloom Filter(CBF), Spectral Bloom Filter(SBF) and Dynamic Counting Filter(DCF), gives some examples and applications in data stream which include duplicate items detecting and frequent items mining.
该文分析比较计数型Bloom过滤器、光谱Bloom过滤器和动态计数过滤器的异同点及适用场合,介绍Bloom过滤器在重复项检测及频繁项挖掘中的应用,总结Bloom过滤器给数据流带来的挑战,包括元素突发问题及数据流相异元素数目变化问题。
补充资料:计数
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