All roads lead to Rome - New search methods for the optimal triangulation problem

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F12%3A00384920" target="_blank" >RIV/67985556:_____/12:00384920 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.ijar.2012.06.006" target="_blank" >http://dx.doi.org/10.1016/j.ijar.2012.06.006</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.ijar.2012.06.006" target="_blank" >10.1016/j.ijar.2012.06.006</a>

Jazyk výsledku

angličtina

Název v původním jazyce

All roads lead to Rome - New search methods for the optimal triangulation problem

Popis výsledku v původním jazyce

To perform efficient inference in Bayesian networks by means of a Junction Tree method, the network graph needs to be triangulated. The quality of this triangulation largely determines the efficiency of the subsequent inference, but the triangulation problem is unfortunately NP-hard. It is common for existing methods to use the treewidth criterion for optimality of a triangulation. However, this criterion may lead to a somewhat harder inference problem than the total table size criterion. We therefore investigate new methods for depth-first search and best-first search for finding optimal total table size triangulations. The search methods are made faster by efficient dynamic maintenance of the cliques of a graph. This problem was investigated by Stix,and in this paper we derive a new simple method based on the Bron-Kerbosch algorithm that compares favourably to Stix' approach. The new approach is generic in the sense that it can be used with other algorithms than just Bron-Kerbosch.

Název v anglickém jazyce

All roads lead to Rome - New search methods for the optimal triangulation problem

Popis výsledku anglicky

To perform efficient inference in Bayesian networks by means of a Junction Tree method, the network graph needs to be triangulated. The quality of this triangulation largely determines the efficiency of the subsequent inference, but the triangulation problem is unfortunately NP-hard. It is common for existing methods to use the treewidth criterion for optimality of a triangulation. However, this criterion may lead to a somewhat harder inference problem than the total table size criterion. We therefore investigate new methods for depth-first search and best-first search for finding optimal total table size triangulations. The search methods are made faster by efficient dynamic maintenance of the cliques of a graph. This problem was investigated by Stix,and in this paper we derive a new simple method based on the Bron-Kerbosch algorithm that compares favourably to Stix' approach. The new approach is generic in the sense that it can be used with other algorithms than just Bron-Kerbosch.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BD - Teorie informace

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

International Journal of Approximate Reasoning

ISSN

0888-613X

e-ISSN

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Svazek periodika

53

Číslo periodika v rámci svazku

9

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

17

Strana od-do

1350-1366

Kód UT WoS článku

000311461700005

EID výsledku v databázi Scopus

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