Title :
Fuzzy metagraph and its combination with the indexing approach in rule-based systems
Author_Institution :
Dept. of Commun. Technol., Aalborg Univ.
fDate :
6/1/2006 12:00:00 AM
Abstract :
This paper presents a graph-theoretic construct called a fuzzy metagraph (FM) with the capability of describing the relationships between sets of fuzzy elements instead of only single fuzzy elements. The algebraic structure of FM and its properties are extensively investigated. Subsequently, the FM construct is applied to rule-based systems. First, we propose FM-based knowledge representation in both graphic and algebraic format. The representation is capable of identifying dependencies across compound propositions in the rules. In the algebraic representation, the FM closure matrix is considered a precompiled rule base enabling efficient query processing. An iterative approach is presented to facilitate the construction and expansion of the FM closure matrix, which is a key for real-world applications. Next, we introduce the concept of indexing, which was originally developed for information retrieval (IR), to enable an immediate extraction of relevant entries from the FM closure matrix. The indexing approach is applied in combination with the FM closure matrix. Based on the combination, corresponding inference mechanisms are introduced to achieve instant acquisition of relevant rules over a large collection of rules. The application in rule-based systems indicates that the combination of FM and IR techniques offers advantages for the mathematical analysis of systems
Keywords :
fuzzy reasoning; graph theory; information retrieval; knowledge acquisition; knowledge based systems; knowledge representation; mathematical analysis; matrix algebra; FM algebraic structure; FM closure matrix; FM-based knowledge representation; fuzzy elements; fuzzy metagraph; graph-theoretic construct; indexing approach; inference mechanism; information retrieval; mathematical analysis; precompiled rule base; query processing; rule-based system; Data mining; Fuzzy sets; Fuzzy systems; Graphics; Indexing; Information retrieval; Iterative methods; Knowledge based systems; Knowledge representation; Query processing; Fuzzy graphs; fuzzy reasoning; information retrieval; knowledge representation; rule-based systems.;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
DOI :
10.1109/TKDE.2006.96