Subgraph mining in a large graph: A review

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F22%3A10249920" target="_blank" >RIV/61989100:27240/22:10249920 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/22:10249920

Výsledek na webu

<a href="https://wires.onlinelibrary.wiley.com/doi/full/10.1002/widm.1454?casa_token=dPl7lX0ptm0AAAAA%3ANj0aa5N4eL1DtmOACnI_MNgIb3vgcbuV8dAJhaWZUkR5Gii5sPF7ah9AFCdIUijJx2-d4zyFqZlWCrM" target="_blank" >https://wires.onlinelibrary.wiley.com/doi/full/10.1002/widm.1454?casa_token=dPl7lX0ptm0AAAAA%3ANj0aa5N4eL1DtmOACnI_MNgIb3vgcbuV8dAJhaWZUkR5Gii5sPF7ah9AFCdIUijJx2-d4zyFqZlWCrM</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/widm.1454" target="_blank" >10.1002/widm.1454</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Subgraph mining in a large graph: A review

Popis výsledku v původním jazyce

Large graphs are often used to simulate and model complex systems in various research and application fields. Because of its importance, frequent subgraph mining (FSM) in single large graphs is a vital issue, and recently, it has attracted numerous researchers, and played an important role in various tasks for both research and application purposes. FSM is aimed at finding all subgraphs whose number of appearances in a large graph is greater than or equal to a given frequency threshold. In most recent applications, the underlying graphs are very large, such as social networks, and therefore algorithms for FSM from a single large graph have been rapidly developed, but all of them have NP-hard (nondeterministic polynomial time) complexity with huge search spaces, and therefore still need a lot of time and memory to restore and process. In this article, we present an overview of problems of FSM, important phases in FSM, main groups of FSM, as well as surveying many modern applied algorithms. This includes many practical applications and is a fundamental premise for many studies in the future. This article is categorized under: Algorithmic Development &gt; Association Rules Algorithmic Development &gt; Structure Discovery

Název v anglickém jazyce

Subgraph mining in a large graph: A review

Popis výsledku anglicky

Large graphs are often used to simulate and model complex systems in various research and application fields. Because of its importance, frequent subgraph mining (FSM) in single large graphs is a vital issue, and recently, it has attracted numerous researchers, and played an important role in various tasks for both research and application purposes. FSM is aimed at finding all subgraphs whose number of appearances in a large graph is greater than or equal to a given frequency threshold. In most recent applications, the underlying graphs are very large, such as social networks, and therefore algorithms for FSM from a single large graph have been rapidly developed, but all of them have NP-hard (nondeterministic polynomial time) complexity with huge search spaces, and therefore still need a lot of time and memory to restore and process. In this article, we present an overview of problems of FSM, important phases in FSM, main groups of FSM, as well as surveying many modern applied algorithms. This includes many practical applications and is a fundamental premise for many studies in the future. This article is categorized under: Algorithmic Development &gt; Association Rules Algorithmic Development &gt; Structure Discovery

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

ISSN

1942-4787

e-ISSN

1942-4795

Svazek periodika

12

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

24

Strana od-do

—

Kód UT WoS článku

000765699100001

EID výsledku v databázi Scopus

—