Entity fine granularity classifying method and system for knowledge base updating

Abstract

The invention provides an entity fine granularity classifying method and system for knowledge base updating. The entity fine granularity classifying method for knowledge base updating comprises the steps that an entity is recognized in a text; the recognized entity, an entity, relevant to the recognized entity, in a knowledge base and the category, of the relevant entity, in the knowledge serve as nodes to construct a depending diagram, wherein the weight of an edge in the depending diagram shows the degree of correlation of the two nodes connected with the edge; the category of the recognized entity is obtained by executing restarting random walking on the depending diagram. According to the entity fine granularity classifying method and system for knowledge base updating, the defect that in the prior art, fine granularity classification of an entity can not be achieved easily under the condition that the context of the entity is not sufficient is overcome, and the accuracy of entity fine granularity classification is improved.

Description

technical field [0001] The invention relates to the technical field of information processing, in particular to an entity fine-grained classification method and system for updating knowledge bases. Background technique [0002] A knowledge base is a collection of interconnected knowledge organized and managed by a certain knowledge representation. In the field of knowledge engineering, the elements of knowledge description generally include classification, entity, relationship, attribute and other elements, where classification is used for semantic grouping or semantic labeling of knowledge items in the knowledge base. Knowledge bases play a vital role in many fields. For example, in information retrieval, knowledge bases can help search engines understand user queries, perceive user query intentions, perform query expansion and query question answering, etc.; in addition, knowledge bases play an important role in data analysis. , Public opinion monitoring, deep network res...

AI Technical Summary

Problems solved by technology

Among them, the method based on heuristic rules directly classifies entities through the defined syntax patterns. This method is simple to operate, but requires manual maintenance and definition of a large number of rules.

The method based on weak supervision extracts the context of the entity, and uses the lexical and syntactic features of the context to calculate the classification information of the entity. However, the accuracy of this method is low, and this method will be difficult to infer the classification of the entity in the absence of context. information

[0006] To sum up, the existing entity coarse-grained classification method is not suitable for updating the knowledge base, and the existing entity fine-grained classification method has low accuracy

Images