Auto-tagging articles using latent semantic indexing and ontology

Abstract

Tagging plays a crucial role in the success of social network and social collaboration. This paper proposes an auto-tagging methodology for articles using Latent Semantic Indexing (LSI) and ontology. The proposed methodology consists of pre-processing and tagging process. In pre-processing process, the LSI vector is created for article classification. The tagging process suggests some ontological tags. An accuracy evaluation of auto-tagging compared with manual-tagging is discussed. The experimental results show that the proposed auto-tagging methodology returns high accuracy and recall. © 2014 Springer International Publishing Switzerland.