Abstract :
Lots of work has been done in the field of AI, knowledge bases, natural languages, semantics and logic by using the tree search method, pattern recognition, neural networks, etc., and we are now beginning to have systems which can understand the meaning of a word or a sentence as a human does, but these systems are not flexible or mature enough for real use, and so not yet applicable for real use. This problem mainly comes from the processing methods used, the methods used to understand words and sentences, and the non-dynamic recognition behaviours. So, in this paper, I introduce a semantic and logic processing method, using neural networks, which has a unique way of transforming words and sentences into neural networks and dynamical behaviourism-accomplishing objectives. As a result of these processes, I found that a sentence has a meaning that is related to certain knowledge, and this sentence-to-knowledge transformation has a unique knowledge compression method. Therefore, I also introduce a knowledge compression method in semantics and logic
Keywords :
formal logic; knowledge engineering; natural languages; neural nets; artificial intelligence; dynamical behaviourism; knowledge bases; knowledge compression method; logic preprocessor; natural language understanding; neural networks; nondynamic recognition behaviour; pattern recognition; semantic preprocessor; sentence meaning; sentence-to-knowledge transformation; tree search method; word meaning; Logic; Neural networks; Symmetric matrices;
