Query-oriented text summarization using sentence extraction technique

Today there is a huge amount of information from a lot of various resources such as World Wide Web, news articles, e-books and emails. On the one hand, human beings face a shortage of time, and on the other hand, due to the social and occupational needs, they need to obtain the most important information from various resources. Automatic text summarization enables us to access the most important content in the shortest possible time. In this paper a query-oriented text summarization technique is proposed by extracting the most informative sentences. To this end, a number of features are extracted from the sentences, each of which evaluates the importance of the sentences from an aspect. In this paper 11 of the best features are extracted from each of the sentences. This paper has shown that use of more suitable features leads to improved summaries generated. In order to evaluate the automatic generated summaries, the ROUGE criterion has been used.