An optimization of apriori algorithm through the usage of parallel I/O and hints

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2475, Issue , 2002, Pages 449-452

  Pérez, María S ^a   Pons, Ramón A ^a   García, Félix ^b   Carretero, Jesús ^b   Córdoba, María L ^a  

^a UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

^b UNIVERSIDAD CARLOS III DE MADRID   (Spain)

Author keywords

[No Author keywords available]

Indexed keywords

ASSOCIATION RULES; DIGITAL STORAGE; LEARNING ALGORITHMS;

APRIORI ALGORITHMS; ASSOCIATION RULE ALGORITHM; E SYSTEMS; INPUT DATAS; PARALLEL I/O; STORAGE SYSTEMS;

ROUGH SET THEORY;

EID: 26944475666     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-45813-1_59     Document Type: Conference Paper

References (4)

1. Christian Borgelt’s Homepage http://fuzzy.cs.uni-magdeburg.de/borgelt.
2. Maria S. Perez et al. A New MultiAgent Based Architecture for High Performance I/O in clusters. In Proceedings of the 2nd International Workshop on MSA’01, 2001.
3. Maria S. Perez et al. A Proposal for I/O Access Profiles in Parallel Data Mining Algorithms. In 3rd ACIS International Conference on SNPD’02, June 2002.
4. Rakesh Agrawal et al. Mining Association Rules between Sets of Items in Large Databases. In The ACM SIGMOD International Conference on Management of Data, 1993.