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Full-Text Articles in Databases and Information Systems
Cascade Artmap: Integrating Neural Computation And Symbolic Knowledge Processing, Ah-Hwee Tan
Cascade Artmap: Integrating Neural Computation And Symbolic Knowledge Processing, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
This paper introduces a hybrid system termed cascade adaptive resonance theory mapping (ARTMAP) that incorporates symbolic knowledge into neural-network learning and recognition. Cascade ARTMAP, a generalization of fuzzy ARTMAP, represents intermediate attributes and rule cascades of rule-based knowledge explicitly and performs multistep inferencing. A rule insertion algorithm translates if-then symbolic rules into cascade ARTMAP architecture. Besides that initializing networks with prior knowledge can improve predictive accuracy and learning efficiency, the inserted symbolic knowledge can be refined and enhanced by the cascade ARTMAP learning algorithm. By preserving symbolic rule form during learning, the rules extracted from cascade ARTMAP can be compared …
Inductive Neural Logic Network And The Scm Algorithm, Ah-Hwee Tan, Loo-Nin Teow
Inductive Neural Logic Network And The Scm Algorithm, Ah-Hwee Tan, Loo-Nin Teow
Research Collection School Of Computing and Information Systems
Neural Logic Network (NLN) is a class of neural network models that performs both pattern processing and logical inferencing. This article presents a procedure for NLN to learn multi-dimensional mapping of both binary and analog data. The procedure, known as the Supervised Clustering and Matching (SCM) algorithm, provides a means of inferring inductive knowledge from databases. In contrast to gradient descent error correction methods, pattern mapping is learned by an inductive NLN using fast and incremental clustering of input and output patterns. In addition, learning/encoding only takes place when both the input and output match criteria are satisfied in a …