Fibonacci search
E337573
Fibonacci search is a divide-and-conquer search algorithm for sorted arrays that uses Fibonacci numbers to determine probe positions instead of midpoints.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Fibonacci search canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T3214196 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fibonacci search Context triple: [Fibonacci sequence, isUsedInAlgorithm, Fibonacci search]
-
A.
Fibonacci sequence
The Fibonacci sequence is an infinite series of numbers where each term is the sum of the two preceding ones, widely used in mathematics, art, and design due to its connection with the golden ratio and natural growth patterns.
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B.
Fibonacci heap
A Fibonacci heap is an advanced data structure for implementing priority queues that supports very fast amortized running times for operations like insert and decrease-key, making it useful in algorithms such as Dijkstra’s shortest path.
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C.
Marzullo's algorithm
Marzullo's algorithm is a method for selecting the most likely correct time interval from multiple, possibly conflicting time sources, commonly used in clock synchronization systems.
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D.
Berlekamp–Massey algorithm
The Berlekamp–Massey algorithm is a key algorithm in coding theory and cryptography used to efficiently determine the shortest linear feedback shift register that generates a given binary sequence.
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E.
Knuth–Morris–Pratt algorithm
The Knuth–Morris–Pratt algorithm is a classic linear-time string-searching algorithm that efficiently finds occurrences of a pattern within a text by precomputing a prefix function to avoid redundant comparisons.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Fibonacci search Target entity description: Fibonacci search is a divide-and-conquer search algorithm for sorted arrays that uses Fibonacci numbers to determine probe positions instead of midpoints.
-
A.
Fibonacci sequence
The Fibonacci sequence is an infinite series of numbers where each term is the sum of the two preceding ones, widely used in mathematics, art, and design due to its connection with the golden ratio and natural growth patterns.
-
B.
Fibonacci heap
A Fibonacci heap is an advanced data structure for implementing priority queues that supports very fast amortized running times for operations like insert and decrease-key, making it useful in algorithms such as Dijkstra’s shortest path.
-
C.
Marzullo's algorithm
Marzullo's algorithm is a method for selecting the most likely correct time interval from multiple, possibly conflicting time sources, commonly used in clock synchronization systems.
-
D.
Berlekamp–Massey algorithm
The Berlekamp–Massey algorithm is a key algorithm in coding theory and cryptography used to efficiently determine the shortest linear feedback shift register that generates a given binary sequence.
-
E.
Knuth–Morris–Pratt algorithm
The Knuth–Morris–Pratt algorithm is a classic linear-time string-searching algorithm that efficiently finds occurrences of a pattern within a text by precomputing a prefix function to avoid redundant comparisons.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
algorithm for sorted arrays
ⓘ
divide-and-conquer algorithm ⓘ search algorithm ⓘ |
| advantage |
can be efficient on systems where addition and subtraction are cheaper than division
ⓘ
can reduce the number of element comparisons compared to linear search ⓘ uses only addition and subtraction to compute probe indices ⓘ |
| assumes | elements are comparable with a total order ⓘ |
| averageCaseTimeComplexity | O(log n) ⓘ |
| basedOn | Fibonacci sequence ⓘ |
| belongsTo | data structures and algorithms ⓘ |
| bestCaseTimeComplexity | O(1) ⓘ |
| canBeImplementedIn |
iterative form
ⓘ
recursive form ⓘ |
| category | comparison-based search algorithm ⓘ |
| comparesWithBinarySearch |
different probe index computation method
ⓘ
similar asymptotic time complexity ⓘ |
| comparisonType | compares target with element at Fibonacci-based index ⓘ |
| contrastsWith | binary search ⓘ |
| determinesProbePositionsBy |
Fibonacci numbers
ⓘ
linked to:
Fibonacci sequence
|
| doesNotUse | midpoints for probe positions ⓘ |
| field | computer science ⓘ |
| goal | locate a target value in a sorted array ⓘ |
| introducedInContextOf | computer search algorithms ⓘ |
| isEfficientWhen | array size is large and random access is cheap ⓘ |
| isLessSuitableWhen | data structure does not support O(1) random access ⓘ |
| operatesOn | sorted array ⓘ |
| reducesSearchRangeBy | shifting Fibonacci numbers downward each iteration ⓘ |
| relatedTo |
binary search
ⓘ
exponential search ⓘ interpolation search ⓘ |
| requires |
array to be sorted in non-decreasing order
ⓘ
knowledge of Fibonacci sequence generation ⓘ random access to array elements ⓘ |
| requiresPreprocessing | computation of Fibonacci numbers up to array size ⓘ |
| searchDomain | index range of the array ⓘ |
| searchStrategy | divide-and-conquer ⓘ |
| spaceComplexity | O(1) ⓘ |
| subfield | algorithmic search methods ⓘ |
| terminationCondition | search range size becomes zero or element is found ⓘ |
| timeComplexity | O(log n) ⓘ |
| typicalUseCase | searching large sorted arrays in low-level or memory-constrained environments ⓘ |
| usedIn | algorithm design education ⓘ |
| uses |
Fibonacci numbers
ⓘ
linked to:
Fibonacci sequence
three consecutive Fibonacci numbers to control the search range ⓘ |
| usesIndexComputation | offset from the start of the current range determined by a Fibonacci number ⓘ |
| usesMathematicalConcept |
Fibonacci numbers
ⓘ
linked to:
Fibonacci sequence
properties of Fibonacci sequence indices ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Fibonacci search Description of subject: Fibonacci search is a divide-and-conquer search algorithm for sorted arrays that uses Fibonacci numbers to determine probe positions instead of midpoints.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.