Validation on Efficient Text Classification Based on Latent Semantic with a Graph of Co-occurring Terms

Abstract

We have proposed a method to raise the accuracy of text classification based on latent topic information, introducing several techniques such as extracting important words with PageRank algorithm and reducing the size of target documents by replacing them with important sentences in themselves. We have experimented on text classification with Reuters-21578 data set and confirmed that our proposed method worked to raise the accuracy of text classification. In this paper, we aim to verify our method with additional experiments using 20 Newsgroups data set and report the experimental result.