Topic modeling combined with classification technique for extractive multi-document text summarization

Abstract

The qualities of human readable summaries available in the datasets are not up to the mark, leading to issues in creating an accurate model for text summarization. Although recent works have been largely built upon this issue and set up a strong platform for further improvements, they still have many limitations. Looking in this direction, the paper proposes a novel methodology for summarizing a corpus of documents to generate a coherent summary using topic modeling and classification technique. The objectives of the propose work are highlighted below: The outcomes of the empirical work show that the proposed model is more promising compared to the well-known text summarization models.