A New Text Summarization Approach based on Relative Entropy and Document Decomposition

In the era of the fourth industrial revolution, the rapid relay on using the Internet made online resources explosively grow. This revolution emphasized the demand for new approaches to utilize the use of online resources such as texts. Thus, the difficulty to compare unstructured resources (text) is urging the demand of proposing a new approach, which is the core of this paper. In fact, text summarization technology is a vital part of text processing, therefore. The focus is on the semantic information not just on the basic information. It requires mining topic features in order to obtain topic-words and topic-sentences relationships. This automatic text summarization is document decomposition according to relative entropy analysis; which means measuring the difference of the probability distribution to measure the correlation between sentences. This paper introduced a new method for document decomposition, which categorizes the sentences into three types of content. The performance demonstrated the efficiency of using the relative entropy of the topic probability distribution over sentences, which enriched the horizon of text processing and summarization research field.