Title :
Reorganizing knowledge to improve performance
Author :
Lopez-Suarez, A. ; Kamel, M.
Author_Institution :
Mackenzie Financial Corp., Toronto, Ont., Canada
Abstract :
This paper presents a method to reorganize rules in knowledge bases with the objective of improving their performance. Knowledge reorganization is achieved through the combination of rule compression and abstraction techniques. The effectiveness of this methodology is evaluated in terms of pattern matching activity and execution times using knowledge bases from several application areas
Keywords :
inference mechanisms; knowledge based systems; pattern matching; performance evaluation; abstraction techniques; application areas; execution times; knowledge bases; knowledge reorganisation; pattern matching; performance improvement; rule compression; Algorithm design and analysis; Assembly; Compression algorithms; Engines; Inference algorithms; Knowledge based systems; Pattern matching; Performance gain; System performance;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
