Abstract:
Summaries are considered as useful indicators of the document content.
Traditionally, summaries are created by humans, through reading a text and
identifying the most important points in it. But the information overloading makes
such manual work very difficult. Many attempts have been made to automate the
summarization task.
This project aims at proposing a methodology for automatic text summarization
based on extractive methods. Extractive summarization needs the selection of a subset
of important, meaningful sentences from the source text. The work presents a method
for automatic text summarization of a single computer science article using statistical
and linguistic approach. About 50 experts' persons summaries were used to evaluate
the proposed method. Our results show that using the combinational statistical and
linguistic methods is better than using each method alone.
Description:
no of pages 110, 25109, تكنولوجيا المعلومات 16/2011, in the store
