Intelligent E-news Summarization

People tend to read multiple news articles on a certain news topic since a single news article may not contain all the important information. A summary of all the articles related to the topic will save the time and energy when referring to a certain news topic. Text summarization is a way of minimizing a textual document to a meaningful summary by preserving its information content and the overall meaning. In this research an extractive based multi-document summary is presented to summarize e-news articles from different e-news sites which describe about the same topic. The system was developed using a hybrid model; a graph-based approach and a feature-based approach combined together. The general ideas behind these methods have been described in this paper. The ROUGE metric was used to evaluate the performance of the summaries generated by the system.