Knowledge Base Construction and Partial Order Structure Graph Generation Method Based on Incremental Learning

Abstract

The invention discloses a method for constructing a knowledge base based on incremental learning and generating a partial sequence structure graph. It adopts the idea of ​​incremental learning based on the covering principle to guide the covering operation of attributes and object sets, and completes special functions such as attribute libraries through special covering relations. The construction of the set further completes the generation of the formal background, and completes the deletion of redundant patterns; it is constructed on the basis of the formal background, and its computer generation algorithm obtains the precise coordinate positioning of each concept node by calculating the hierarchical pattern matrix. Layers, nodes, connections and other elements, as well as the introduction of incremental learning algorithms, complete the dynamic construction of partial order structure graphs. Compared with the prior art, the present invention combines the incremental learning based on the coverage principle and the construction algorithm of the partial order structure graph, which can realize the dynamic construction of the knowledge concept base and complete the automatic generation of the hierarchical pattern matrix; realize the partial order structure Incremental construction of graphs.

Description

technical field [0001] The invention relates to the technical field of dynamic construction of knowledge bases and progressive construction of partial sequence structure diagrams, in particular to a dynamic construction of knowledge bases based on incremental learning and a method for progressive generation of partial sequence structure diagrams. Background technique [0002] Starting from the philosophical principles of human cognition, the process of learning knowledge is gradual, and it is impossible to learn all the knowledge at once, and the initial learning is to learn a part first, forming a fixed model, and the subsequent knowledge learning is carried out on the original basis The process of pattern classification, from this learning process, the learned knowledge will become more and more complete, and the pattern learning will become more abundant. When the amount of learning reaches a certain limit, the pattern will gradually become complete, and the redundant know...

AI Technical Summary

Problems solved by technology

However, at present, the composition of the partial order diagram needs to obtain complete concepts at one time for batch construction, that is, the prerequisite for the construction of the formal background needs to obtain all the concepts, and generate attribute partial order structure diagrams in batches, which does not fully comply with the progressive construction knowledge model. way of thinking

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