De-word classification algorithm based on the electric power of large data library retrieval

Abstract

In order to improve the performance of text classification and information retrieval in big data of electric power domain, we propose a novel Chinese language classification algorithm - De-word classification algorithm. Focusing on the key role played by the De-word in modern Chinese language, this algorithm examines Chinese text classification method from a unique angle. Besides, on the basis of traditional weighted algorithm, it designs a novel relevance weighting model - De-TFIDF, and achieves a higher correlation in text information retrieval. Experiments show that, De-word classification algorithm significantly improves the efficiency of text classification, significantly improved information retrieval performance.