Abstract:

[Objective] Chinese short text has the problem of feature sparsity, constructing high-quality short text feature representation will be of great significance to the short text classification and short text recommendation, etc. [Methods] To solve this problem, this paper proposes a feature enhancement method for short text based on knowledge graph and topic model. The proposed method uses the knowledge graph to obtain external knowledge for short text feature expansion and uses the topic model to mine the semantic feature in the short text. Finally, the feature-enhanced vector is generated through vector concatenation. [Conclusions] This paper applies the proposed method to the Chinese short text classification task. The comparative experiment results show that the proposed method can better represent short texts.

Key words: text feature enhancement, topic model, short text classification, knowledge graph