Research any topic before you write.

Find related topics. | Discover entities. | See connections. | Build a topical map.

Kernelization

In computer science, a kernelization is a technique for designing efficient algorithms that achieve their efficiency by a preprocessing stage in which inputs to the algorithm are replaced by a smaller input, called a "kernel". The result of solving the problem on the kernel should either be the same as on the original input, or it should be easy to…

Science, More examples & Definition

Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Research this topic

Explore the main themes, entities and connections around Kernelization. Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.

More examples

Vertex coverSunflower lemmaFeedback vertex setPathBidimensional
6 related topics

Definition

Flum & Grohe (2006Decision problemComputable function
3 related topics

Kernelizability and fixed-parameter tractability are equivalent

DecidableEmpty string
2 related topics

Overview

Computer scienceAlgorithmsParameterized complexity theoryPolynomial timeFixed-parameter tractable
6 related topics

Topics to explore

Browse the full topic structure. Each item opens a new analysis centered on that subject.

Overview

Definition

Kernelizability and fixed-parameter tractability are equivalent

More examples

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

Map overview Semantic statistics

Kernelization

Nodes22
Edges21
Triples160
Avg. degree1.91
Density0.090909
Components1

How this topic connects Entity context

See the strongest relationship patterns around the current topic before diving into the raw triples.

Kernelization

Top relations

related to References · 100
Kernelization → Abu-Khzam, ACM Symposium, ACM Transactions, ACM-SIAM Symposium, Algorithms, Bart, Bidimensionality, Bodlaender, Buss, Chen, Chris, Cite, CiteSeerX, Collins, Computer, Computer Science, Computing, Daniel, Danny, Dell
related to Further reading · 27
Kernelization → Cambridge University Press, Chapter, Chapters, Daniel, Fedor, Fixed-Parameter Algorithms, Fomin, Invitation, ISBN, Kowalik, Lokshtanov, Lukasz, Marcin, Marek, Marx, Meirav, Michal, Oxford University Press, Parameterized Algorithms, Parameterized Preprocessing
related to Example: vertex cover · 11
Kernelization → An, Buss, Every, For, However, If, In, NP-hard, The, This, Thus
related to Kernelization for structural parameterizations · 6
Kernelization → For, It, The, There, This, While
related to Flum–Grohe notation · 5
Kernelization → Flum, Grohe, In, Sigma, The
related to Downey–Fellows notation · 4
Kernelization → Downey, Fellows, In, Sigma
related to Kernelizability and fixed-parameter tractability are equivalent · 4
Kernelization → First, Since, That, The
is a · 1
Kernelization → technique for designing efficient algorithms that achieve their efficiency by a preprocessing stage in which inputs to the algorithm are replaced by a smaller input
related to Definition · 1
Kernelization → In
see also · 1
Kernelization → Iterative

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

displaystyle problem vertex kernel algorithm cover size fixed-parameter kernels vertices edges time parameterized parameter graph polynomial tractable doi algorithms 10

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Kernelizationis atechnique for designing efficient algorithms that achieve their efficiency by a preprocessing stage in which inputs to the algorithm are replaced by a smaller input0.90text
Kernelizationrelated to DefinitionIn0.60section
Kernelizationrelated to Downey–Fellows notationIn0.60section
Kernelizationrelated to Downey–Fellows notationDowney0.60section
Kernelizationrelated to Downey–Fellows notationFellows0.60section
Kernelizationrelated to Downey–Fellows notationSigma0.60section
Kernelizationrelated to Example: vertex coverBuss0.60section
Kernelizationrelated to Example: vertex coverIn0.60section
Kernelizationrelated to Example: vertex coverThe0.60section
Kernelizationrelated to Example: vertex coverThis0.60section
Kernelizationrelated to Example: vertex coverNP-hard0.60section
Kernelizationrelated to Example: vertex coverHowever0.60section

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

    Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.

    Min side: 3
    For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.