Paper Info
Title
A Concurrent Approach to the Key-Preserving Attribute-Oriented Induction Method
Abstract
Attribute-Oriented Induction (AOI) reduces the search space of large data to produce a minimal rule set. Classical AOI techniques only consider attributes that can be generalised but eliminates keys to relations. The Key-Preserving AOI (AOI-KP) preserves keys of the input relation and relate them to the rules for subsequent data queries. Previously, the sequential nature of AOI-KP affected performance on a single processor machine. More significantly, time was spent doing I/O to files linked to each generated rule. AOI-KP is O (np) and storage requirement O (n), where n and p represent the number of input and generalised tuples respectively. We present two enhanced AOI-KP algorithms, concAOI-KP (concurrent AOI-KP) and onLineConcAOI-KP of orders O (np) and O (n) respectively. The two algorithms have storage requirement O (p) and O (q), q = p*r, 0r≤ l respectively. A prototype support tool exists and initial results indicate substantially increased utilisation of a single processor.
Year
Venue
Keywords
2000
PAKDD
aoi-kp affected performance,key-preserving aoi,concurrent approach,large data,generalised tuples,enhanced aoi-kp algorithm,key-preserving attribute-oriented induction method,concurrent aoi-kp,orders o,input relation,classical aoi technique,storage requirement o,search space
Field
DocType
Volume
Discrete mathematics,Tuple,Attribute oriented induction,Execution time,Mathematics,Concept hierarchy
Conference
1805
ISSN
ISBN
Citations 
0302-9743
3-540-67382-2
0
PageRank 
References 
Authors
0.34
7
2
Name
Order
Citations
PageRank
Maybin K. Muyeba1477.61
John A. Keane269592.81