
	Where results make sense

Topic: Bloom filter

	Bloom filter - Wikipedia, the free encyclopedia
		The Bloom filter, conceived by Burton H. Bloom in 1970, is a space-efficient probabilistic data structure that is used to test whether an element is a member of a set.
		A Bloom filter to which a dictionary of correct words have been added will accept all words in the dictionary and reject almost all words which are not, which is good enough in some cases.
		Bloom filters also have the unusual property that the time needed to either add items or to check whether an item is in the set is a fixed constant, O(k), completely independent of the number of items already in the set.
	en.wikipedia.org /wiki/Bloom_filter#Bloomier_filters (2164 words)

	perl.com: Using Bloom Filters
		Bloom filters allow you to perform membership tests in just a fraction of the memory you'd need to store a full list of keys, so you can avoid the performance hit of having to use a disk or database to do your lookups.
		Bloom filters are named after Burton Bloom, who first described them in a 1970 paper entitled Space/time trade-offs in hash coding with allowable errors.
		When using Bloom filters, we very frequently have a desired false-positive rate in mind and we are also likely to have a rough idea of how many keys we want to add to the filter.
	www.perl.com /pub/a/2004/04/08/bloom_filters.html (1625 words)

	Bloom filter: Facts and details from Encyclopedia Topic (Site not responding. Last check: 2007-08-30)
		Bloom filters also have the unusual property that the time needed to either add items or to check whether an item is in the set is a fixed constant, EHandler: no quick summary.
		Counting filters provide a way to implement a delete operation on a Bloom filter without recreating the filter afresh.
		The space required for a Bloomier filter with n-bit values is typically slightly more than the space for 2n Bloom filters.
	www.absoluteastronomy.com /encyclopedia/b/bl/bloom_filter.htm (2667 words)

	Bloom Filters as Summaries
		The advantage of Bloom filters is that they provide a tradeoff between the memory requirement and the false positive ratio (which induces false hits).
		We experimented with three configurations for Bloom filter based summaries: the number of bits being 8, 16, and 32 times the average number of documents in the cache (the ratio is also called a ``load factor'').
		The Bloom filter based summaries have virtually the same cache hit ratio as the exact-directory approach, and have slightly higher false hit ratio when the bit array is small.
	www.cs.wisc.edu /~cao/papers/summary-cache/node9.html (1124 words)

	BloomFilter
		Bloom filters allow you to perform membership tests in just a fraction of the memory you'd need to store a full list of keys.
		To enter a key into a Bloom filter, we run it through each one of the k hash functions and treat the result as an offset into the bit vector, turning on whatever bit we find at that position.
		Where c is the false positive rate, k is the number of hash functions, n is the number of keys in the filter, and m is the length of the filter in bits.
	jaspell.sourceforge.net /javadocs/pt/tumba/spell/BloomFilter.html (1792 words)

	URL History Bloom Filters - CommerceNet Wiki
		A Bloom filter that represents the union of two sets can be obtained by taking the OR of the two bit vectors of the original Bloom filters.
		Bloom filters can easily be halved in size, allowing an application to dynamically shrink a Bloom filter.
		Bloom filters can also be used to approximate the intersection between two sets.
	wiki.commerce.net /wiki/URL_History_Bloom_Filters (2371 words)

	Perl.com: Using Bloom Filters
		By exchanging Bloom filters instead of explicit lists of contacts, users can participate in social networking experiments without having to admit to the world who their friends are.
		A Bloom filter encoding someone's contact information can be checked to see whether it contains a given name or email address, but it can't be coerced into revealing the full list of keys that were used to build it.
		If you are passing filters around a network, you will want to optimize them for minimum size; this paper gives a good overview of compressed Bloom filters.
	www.perl.com /lpt/a/2004/04/08/bloom_filters.html (2976 words)

	[No title]
		Bloom Filters A Bloom filter is a very efficient way to store information about the existence of a record in a database.
		Since Bloom filters are specific to any given instance of a zone, the SOA serial number is an essential part of the authentication process.
		Appendix: Bloom Filter Parameters Below is a table showing the false positive probability p for various values of k and ratios of m/n.
	www.cs.columbia.edu /~smb/papers/draft-bellovin-dnsext-bloomfilt-00.txt (2580 words)

	Some Motley Bloom Tricks
		If the filter is to recall the glob in the future then it turns those k bits on in its string.
		Different filters built at different places or different times can be ored together to produce a filter that will recognize any globs recognized by any of its ancestors.
		Oring filters together results in higher densities but this may be ameliorated by reducing the density of contributing filters.
	www.cap-lore.com /code/BloomTheory.html (1005 words)

	Bloom Filters for finding annotations. (Site not responding. Last check: 2007-08-30)
		Abstractly a Bloom filter is a mutable object that maps strings onto bits.
		A bloom filter can also have strings added which causes the filter to respond true to that string in the future.
		The density of the merged filter will be greater than that of the inputs and thus either the inputs or the outputs will have a non optimal density.
	www.cap-lore.com /code/BloomAnno.html (615 words)

	Bloom Air Filter
		Bloomair - Filter (BAF) is a simple, effective, light weight, economical, reliable and convenient breathing air filter which works to get instant clean, fresh, vigour and healthy air from polluted indoor and outdoor atmosphere.
		BAF is an ideal and protective filter mask which can be used to live in polluted atmosphere without deteoriorating the functional rights of the nose, lung and immune system.
		BAF pouch, BAF cushionet and layers of the BAF Pad filter the dust nearly 0.5 micron particles recorded in the laboratory upto 92% - 95% filtration, which are not visible to the naked eyes and most of them are injurious to health.
	www.genecarequalityhealth.com /BAF.html (439 words)

	BloomFilter (MG4J 1.0.1)
		Instances of this class represent a set of character sequences (with false positives) using a Bloom filter.
		Bloom filters have an expected error rate, depending on the number of hash functions used, on the filter size and on the number of elements in the filter.
		Creates a new Bloom filter with given number of hash functions and expected number of elements.
	mg4j.dsi.unimi.it /docs/it/unimi/dsi/mg4j/util/BloomFilter.html (366 words)

	Bloom Filters - the math
		The salient feature of Bloom filters is that there is a clear tradeoff between m and the probability of a false positive.
		It is clear that Bloom filters require very little storage per key at the slight risk of some false positives.
		For instance for a bit array 10 times larger than the number of entries, the probability of a false positive is 1.2% for 4 hash functions, and 0.9% for the optimum case of 5 hash functions.
	www.cs.wisc.edu /~cao/papers/summary-cache/node8.html (729 words)

	CS 535: Machine Problem 2 (Bloom Filters)
		In Lecture 5 we learned about bloom filters and their uses for string/signature matching.
		Bloom filters are very good at performing large membership queries very quickly.
		Since the bloom filter uses a hash function to set a bit vector, a simple hash function will also need to be implemented.
	www.arl.wustl.edu /projects/fpx/cse535/mp/mp2/mp2.html (2031 words)

	Space/time Trade-offs in Hash Coding with Allowable Errors
		Bloom filters are used as summaries for the set of services offered by a node.
		Bloom filters describe membership information of A using a bit vector V of length m.
		We introduce compressed Bloom filters, which improve performance when the Bloom filter is passed as a message, and its transmission size is a limiting factor.
	people.cs.uchicago.edu /~matei/PAPERS/bf.doc (2138 words)

	Lemonodor: Bloom Filters
		Beyond that, you'll want to look at Maciej Ceglowski's “Using Bloom Filters” article on perl.com, which is a good tutorial and also lists several references.
		Our Bloom filter class will consist of three things: the filter's bitmap, the maximum size of the bitmap, and a list of the hash functions the filter is using.
		the key's bitmap with the filter's current bitmap, and if the result is equal to the key's bitmap then the key is (probably) in the filter.
	lemonodor.com /archives/000881.html#000881 (847 words)

	[No title]
		This would be slower than wildcard searches without bloom filters, but it wouldn't cause the wildcard search on the RLI to return an error that the command is unsupported.
		Also the cost of maintaining the filter may be high if the available RLIs at any point is dynamic, since whenever an RLI comes up or disappears all the bloom filters have to be recomputed.
		If there are partition specific bloom filters I either continue the above (simple) method, which means all partitioned bloom filters are just as big as the global one (meaning no performance gain at all), or I try to maintain the size of each filter separately.
	mailman.isi.edu /pipermail/rls-internal/2002-September.txt (7344 words)

	Caltech Parallel and Distributed Systems Group - Adaptive Bloom filter
		A Bloom filter is a simple randomized data structure that answers membership query with no false negative and a small false positive probability.
		In this paper, we generalize the traditional Bloom filter to Adaptive Bloom Filter, which incorporates the information on the query frequencies and the membership likelihood of the elements into its optimal design.
		The traditional Bloom filter for data sets with irregular query patterns and non-uniform membership likelihood can be further optimized.
	resolver.caltech.edu /CaltechPARADISE:2006.ETR072 (227 words)

	Bloom filter (Site not responding. Last check: 2007-08-30)
		A Bloom filter is good for secret sharing: giving a Bloom filter lets someone see if you have an item (it is found in the Bloom filter), but it is impractical to recreate the whole collection.
		Trade-offs and engineering techniques with links to sites with recent papers, hash functions, etc. Another explanation typo: probability of false positive is missing a minus sign; exponent should be...
		Paul E. Black, "Bloom filter", in Dictionary of Algorithms and Data Structures [online], Paul E. Black, ed., U.S. National Institute of Standards and Technology.
	www.nist.gov /dads/HTML/bloomFilter.html (170 words)

	Eggs Unlimited - bloom-filter
		The current population - the number of objects added to the filter.
		The probability of false positives for the given population size.
		Nice exposition of Bloom Filter False Positive Probability.
	www.call-with-current-continuation.org /eggs/bloom-filter.html (365 words)

	Space-Code Bloom Filter for Efficient Per-Flow Traffic Measurement - Kumar, Xu, Wang, Spatscheck, Li (ResearchIndex) (Site not responding. Last check: 2007-08-30)
		We introduce a novel technique for measuring perflow traffic approximately, for all flows regardless of their sizes, at very high-speed (say, OC768).
		The core of this technique is a novel data structure called Space Code Bloom Filter (SCBF).
		Kumar, J. Xu, J. Wang, O. Spatscheck, and L. Li, "Space-code Bloom filter for efficient per-flow traffic measurement," in Infocom, 2004.
	citeseer.ist.psu.edu /639283.html (486 words)

	Bloom filter for HDRI images - GameDev.Net Discussion Forums
		Whilst the actual effects might not be physically accurate, they do seem to at least be close to the physical effects.
		Fwiw, in my opinion that's actually a fairly bad implementation of the bloom and glare effect.
		I forget which "big name" in games/graphics programming said it, but they declared "HDRI bloom" as being the "next lens flare"...
	www.gamedev.net /community/forums/topic.asp?topic_id=331249 (628 words)

	An Optimal Bloom Filter Replacement (Site not responding. Last check: 2007-08-30)
		This paper considers space-efficient data structures for storing an approximation S' to a set S such that S subseteq S' and any element not in S belongs to S' with probability at most epsilon.
		The Bloom filter data structure, solving this problem, has found widespread use.
		We also consider three recent generalizations of Bloom filters.
	www.itu.dk /people/annao/Publications/Filter.html (139 words)

	[No title]
		They would like to save their results and queries for future use, use annotation facilities, the ability to transfer OED text segments to other documents, tools to sort and filter quotations, and tools for statistical analysis of variables.
		Since these "clever" apprentices are intrinsically difficult to construct (they not only need precision but also accuracy and recall), he suggested a "shallow apprentice" - a system which discovers links through superficial textual analysis (of statistical and lexical properties) without analyzing meaning [Bernstein, 1990].
		Each hypertext page (node) has a Bloom filter hash table where each word is hashed.
	www.e-papyrus.com /hypertext_review/chapter2.html (4325 words)

	Space-Code Bloom Filter for Efficient Traffic Flow Measurement (ResearchIndex)
		Space-Code Bloom Filter for Efficient Traffic Flow Measurement (2003)
		Our paper introduces a novel technique for measuring per-flow traffic approximately, for all flows regardless of their sizes, at very high-speed (say, OC192+).
		The core of this technique is a novel data structure called Space Code Bloom Filter...
	citeseer.ist.psu.edu /630957.html (384 words)

	Kn filter (Site not responding. Last check: 2007-08-30)
		Kn filter Smithsonian Magazine: Explore Art, Science and History..
		Keyboard magazine is the definitive source for information on the hottest musicand music technology, including keyboards, synths, digital pianos, Kn filter.
		Copyright © 2004 Bid Filter Site And Home Sites.
	www.bidfilter.com /Kn-filter.html (260 words)

	SourceForge.net: Python Bloom Filter
		Provide feedback on this page Recently changed page Site Status
		A Bloom Filter implementation in pure python, using only the standard library.
		Support Requests : (0 open / 0 total)
	sourceforge.net /projects/pybloom (76 words)

Try your search on: Qwika (all wikis)