On the practical significance of hypertree vs. tree width

Frontiers in Artificial Intelligence and Applications

Volumn 178, Issue , 2008, Pages 913-914

  Dechter, Rina ^a   Otten, Lars ^a   Marinescu, Radu ^b  

^a Ringgold Standard Institution Informatics   (United States)

^b UNIVERSITY COLLEGE CORK   (Ireland)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BENCHMARKING;

CONSTRAINT NETWORKS; DETERMINISTICS; HYPERTREES; POWER; PROBABILISTIC NETWORK; PROBABILISTICS; TREE-WIDTH;

FORESTRY;

EID: 84978521970     PISSN: 09226389     EISSN: 18798314     Source Type: Book Series    
DOI: 10.3233/978-1-58603-891-5-913     Document Type: Conference Paper

References (4)

1. R. Dechter, L. Otten, and R. Marinescu: ‘On the Practical Significance of Hypertree vs. Tree Width’, Technical Report, University of California, Irvine, (2008).
2. G. Gottlob, M. Grohe, N. Musliu, M. Samer, and F. Scarcello, Hypertree Decompositions: ‘Structure, Algorithms, and Applications’, International Workshop on Graph-Theoretic Concepts in Computer Science, (2005).
3. G. Gottlob, N. Leone, and F. Scarcello, ‘A comparison of structural CSP decomposition methods’, Artificial Intelligence, (2000).
4. K. Kask, R. Dechter, J. Larrosa, and A. Dechter, ‘Unifying tree-decompositions for reasoning in graphical models’, Artificial Intelligence, (2005).