Bloom Filter

as donto believed on

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)

Bloom Filter is tests whether an element is a member of a set.

39 facts·27 predicates·5 sources·7 in dispute

Mostly:rdf:type(4), function(3), has attribute(3)

Inbound mentions (12)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

`alternativeTo`Alternative to(2)

Hash Tableex:hash-table
Trieex:trie

`hasMember`Has Member(2)

Data Structuresex:data-structures
Three Approachesex:three-approaches

`associatedWith`Associated With(1)

False Positiveex:false-positive

`attributeOf`Attribute of(1)

Space Efficiencyex:space-efficiency

`example`Example(1)

Probabilistic Structureex:probabilistic-structure

`hasApproach`Has Approach(1)

Dictionary Optimizationex:dictionary-optimization

`includes`Includes(1)

Algorithmic Recommendationsex:algorithmic-recommendations

`mentions`Mentions(1)

Data Structure Summaryex:data_structure_summary

`moreEfficientThan`More Efficient Than(1)

Trieex:trie

`usedBy`Used by(1)

Md5ex:md5

Other facts (38)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

38 facts

Predicate	Value	Ref
Rdf:type	Data Structure	[1]
Rdf:type	Probabilistic Data Structure	[4]
Rdf:type	Space Efficient Structure	[4]
Rdf:type	Data Structure	[5]
Function	quickly-rule-out-non-existent-keys	[1]
Function	quickly rule out non-existent keys	[3]
Function	adds words as they are added to dictionary	[3]
Has Attribute	bit_array	[4]
Has Attribute	size	[4]
Has Attribute	hash_count	[4]
Initialization Parameter	capacity	[3]
Initialization Parameter	error_rate	[3]
Property	never_false_negatives	[4]
Property	may_have_false_positives	[4]
Supports	membership_test	[4]
Supports	addition	[4]
Has Method	Check	[5]
Has Method	Init	[5]
Used for	Dictionary Lookup	[1]
Used Before	Full Dictionary Lookup	[1]
Alternative to	Trie	[1]
Optimizes	Lookup Efficiency	[1]
Provides	Quick Filtering	[1]
Reduces	Full Lookup Frequency	[1]
Mentioned As	beneficial-for-avoiding-unnecessary-lookups	[2]
Condition for Use	large-dictionary-avoiding-lookups	[2]
Benefit	avoiding-unnecessary-lookups	[2]
Application Context	large-dictionary-scenarios	[2]
Use Case	rule out non-existent keys before dictionary lookup	[3]
Description	tests whether an element is a member of a set	[4]
Class Definition	BloomFilter	[4]
Data Structure	bit-array	[4]
Probability Structure	true	[4]
Algorithm Type	probabilistic-testing	[4]
Approximates	set-membership	[4]
Trades Off	accuracy-for-space	[4]
Allows	false-positives	[4]
Prevents	false-negatives	[4]

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

39 undated

—

typebeam/eda34030-0bc4-4fab-bee6-4766ec39eee1

ex:DataStructure

—

labelbeam/eda34030-0bc4-4fab-bee6-4766ec39eee1

Bloom Filter

—

usedForbeam/eda34030-0bc4-4fab-bee6-4766ec39eee1

ex:dictionary-lookup

—

functionbeam/eda34030-0bc4-4fab-bee6-4766ec39eee1

quickly-rule-out-non-existent-keys

—

usedBeforebeam/eda34030-0bc4-4fab-bee6-4766ec39eee1

ex:full-dictionary-lookup

—

alternativeTobeam/eda34030-0bc4-4fab-bee6-4766ec39eee1

ex:trie

—

optimizesbeam/eda34030-0bc4-4fab-bee6-4766ec39eee1

ex:lookup-efficiency

—

providesbeam/eda34030-0bc4-4fab-bee6-4766ec39eee1

ex:quick-filtering

—

reducesbeam/eda34030-0bc4-4fab-bee6-4766ec39eee1

ex:full-lookup-frequency

—

mentionedAsbeam/495977be-9a3c-4555-9004-9809144cb44a

beneficial-for-avoiding-unnecessary-lookups

—

conditionForUsebeam/495977be-9a3c-4555-9004-9809144cb44a

large-dictionary-avoiding-lookups

—

benefitbeam/495977be-9a3c-4555-9004-9809144cb44a

avoiding-unnecessary-lookups

—

application-contextbeam/495977be-9a3c-4555-9004-9809144cb44a

large-dictionary-scenarios

—

functionbeam/ffa3c62a-28f9-4a35-81a1-fa11dfc5a70a

quickly rule out non-existent keys

—

functionbeam/ffa3c62a-28f9-4a35-81a1-fa11dfc5a70a

adds words as they are added to dictionary

—

useCasebeam/ffa3c62a-28f9-4a35-81a1-fa11dfc5a70a

rule out non-existent keys before dictionary lookup

—

initializationParameterbeam/ffa3c62a-28f9-4a35-81a1-fa11dfc5a70a

capacity

—

initializationParameterbeam/ffa3c62a-28f9-4a35-81a1-fa11dfc5a70a

error_rate

—

typebeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

ex:ProbabilisticDataStructure

—

typebeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

ex:SpaceEfficientStructure

—

descriptionbeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

tests whether an element is a member of a set

—

propertybeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

never_false_negatives

—

propertybeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

may_have_false_positives

—

classDefinitionbeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

BloomFilter

—

hasAttributebeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

bit_array

—

hasAttributebeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

size

—

hasAttributebeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

hash_count

—

supportsbeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

membership_test

—

supportsbeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

addition

—

dataStructurebeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

bit-array

—

probabilityStructurebeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

true

—

algorithmTypebeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

probabilistic-testing

—

approximatesbeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

set-membership

—

trades-offbeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

accuracy-for-space

—

allowsbeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

false-positives

—

preventsbeam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f

false-negatives

—

typebeam/9a30ba69-a5d9-4112-8a96-910a73b0346c

ex:DataStructure

—

hasMethodbeam/9a30ba69-a5d9-4112-8a96-910a73b0346c

ex:check

—

hasMethodbeam/9a30ba69-a5d9-4112-8a96-910a73b0346c

ex:__init__

References (5)

5 references

[1]Eda34030 0bc4 4fab Bee6 4766ec39eee19 facts
ctx:claims/beam/eda34030-0bc4-4fab-bee6-4766ec39eee1
- full textbeam-chunk
  text/plain1 KBdoc:beam/eda34030-0bc4-4fab-bee6-4766ec39eee1
  Show excerpt
  1. **Use a Trie (Prefix Tree)**: If your dictionary contains words with common prefixes, a Trie can be more efficient for lookups. 2. **Hash Table with Custom Hash Function**: Ensure that the hash function is well-distributed to minimize co…
[2]495977be 9a3c 4555 9004 9809144cb44a4 facts
ctx:claims/beam/495977be-9a3c-4555-9004-9809144cb44a
- full textbeam-chunk
  text/plain1 KBdoc:beam/495977be-9a3c-4555-9004-9809144cb44a
  Show excerpt
  Choose the approach that best fits your use case. If you have common prefixes, a Trie might be more efficient. If you have a large dictionary and want to avoid unnecessary lookups, a Bloom filter can be beneficial. Let me know if you need …
[3]Ffa3c62a 28f9 4a35 81a1 Fa11dfc5a70a5 facts
ctx:claims/beam/ffa3c62a-28f9-4a35-81a1-fa11dfc5a70a
- full textbeam-chunk
  text/plain1 KBdoc:beam/ffa3c62a-28f9-4a35-81a1-fa11dfc5a70a
  Show excerpt
  def __init__(self, expected_elements, false_positive_rate): self.dictionary = {} self.bloom_filter = BloomFilter(capacity=expected_elements, error_rate=false_positive_rate) def add_word(self, word, synonym): …
[4]261d8480 79ba 48b8 Ad3d 1d5b8a337a1f18 facts
ctx:claims/beam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f
- full textbeam-chunk
  text/plain1 KBdoc:beam/261d8480-79ba-48b8-ad3d-1d5b8a337a1f
  Show excerpt
  self.is_end_of_word = False def insert_trie(root, word): node = root for char in word: if char not in node.children: node.children[char] = TrieNode() node = node.children[char] …
[5]9a30ba69 A5d9 4112 8a96 910a73b0346c3 facts
ctx:claims/beam/9a30ba69-a5d9-4112-8a96-910a73b0346c
- full textbeam-chunk
  text/plain929 Bdoc:beam/9a30ba69-a5d9-4112-8a96-910a73b0346c
  Show excerpt
  index = int(digest, 16) % self.size self.bit_array[index] = True def check(self, item): for i in range(self.hash_count): digest = hashlib.md5((str(item) + str(i)).encode()).hexdiges…

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Bloom Filter

Inbound mentions (12)

alternativeToAlternative to(2)

hasMemberHas Member(2)

associatedWithAssociated With(1)

attributeOfAttribute of(1)

exampleExample(1)

hasApproachHas Approach(1)

includesIncludes(1)

mentionsMentions(1)

moreEfficientThanMore Efficient Than(1)

usedByUsed by(1)

Other facts (38)

Timeline

References (5)

See also

Keep researching

`alternativeTo`Alternative to(2)

`hasMember`Has Member(2)

`associatedWith`Associated With(1)

`attributeOf`Attribute of(1)

`example`Example(1)

`hasApproach`Has Approach(1)

`includes`Includes(1)

`mentions`Mentions(1)

`moreEfficientThan`More Efficient Than(1)

`usedBy`Used by(1)