ABSTRACT
Thousands of years ago written language was introduced as a way of enhancing and
facilitating communication. Fast forward to the twenty first century much has
changed, especially the flow of data incrementing at fast rate and we have to use the
power of algorithms and hardware technology to understand text more clearly. With
the Information age rising we are being cluttered with humongous data each day with
no sign of it slowing. humans have been trying to create ways on how to handle this
continuous flow of text, image and video. And one of the category of subjects
Regarding text is text summarization, given a document coming up with a reasonable
summarized version of the original document. people have tried different aspects of
summarizing to get a shorter yet an informative definition of document. This paper
tries to utilize using nature inspired algorithms to implement an auto summarizer of
text using pseudo-selected features. The main objective of this research is to use of
cooperative nature-inspired algorithm specifically ant colony algorithm in text
mining problems, in our case, text summarization. And throughout the paper we will
try to show how this system can be achieved as well as show the performance and
effectiveness of the measurement. We have used the standard data used to test
summarization techniques, DUC data and at last comparing it to two algorithms for
further analysis.
