An approach to concept-obtained text summarization

In this paper, we propose a practical approach for extracting the most relevant sentences from the original document to form a summary. The idea of our approach is to obtain concepts of words based on HowNet, and use concept as feature, instead of word. We use conceptual vector space model to form a rough summarization, and then calculate degree of semantic similarity of sentence for reducing its redundancy. Experimental results show that our approach is effective and efficient, and performance of the system is reliable.