Multi-Document summarization based on improved features and clustering

Multi-Document summarization is an emerging technique for understanding the main purpose of many documents about the same topic. This paper proposes a new feature selection method to improve the summarization result. When calculating similarity, we use a modified TFIDF formula which achieves a better result. We adopt two ways for exactly extracting keywords. Experimental results demonstrate that our improved method performs better than the traditional one.