摘要：

Abstract:

【Purpose/significance】Text representation using traditional methods is often unsatisfactory because it ignores the semantic

relationships between words. Constructing text semantic graph based on knowledge graph can solve the problem of semantic deficien⁃

cies.【Method/process】First, a semantic graph with named entities in the text as nodes and semantic relationships between entities as

sides is constructed based on the encyclopedia Knowledge Graph, CN-DBpedia. Second, the concept graph CN-Probase is introduced

to map entities to concepts, and an enhanced Chinese text semantic graph with embedded concept knowledge graph is generated. Final⁃

ly, the method proposed in this paper is validated by using the pattern discovery task of news text as an example.【Result/conclusion】

This study proposed a novel method to construct Chinese text semantic graph based on multiple knowledge graphs.【Innovation/limita⁃

tion】This study implements the semantic representation of text at both entity level and conceptual level, which can be widely used in

nature language processing tasks such as text representation and text analysis. The limitation of this study is that the method we pro⁃

posed only be validated in news texts.