Text Summarization is condensing the source text into a shorter version preserving its
information content and overall meaning. It is very difficult for human beings to manually …

The technology of automatic document summarization is maturing and may provide a
solution to the information overload problem. Nowadays, document summarization plays an …

In paper, we propose an unsupervised text summarization model which generates a
summary by extracting salient sentences in given document (s). In particular, we model text …

The increasing usage of the Internet and social networks has produced a significant amount
of online textual data. These online textual data led to information overload and redundancy …

Featured Application This paper provides applicability of the Real Coded Genetic Algorithm
to the Natural Language Processing Task, ie, Text Summarization. The purpose of text …

In today's scenario the rate of growth of information is expanding exponentially in the World
Wide Web. As a result, extracting valid and useful information from a huge data has become …

Abstract Today, World Wide Web has brought us enormous quantity of on-line information.
As a result, extracting relevant information from massive data has become a challenging …

• Other approaches: Other approaches about keyword extraction mainly combines the
methods mentioned above or use some heuristic knowledge in the task of keyword …

The amount of available multimedia data in different formats and from different sources
increases everyday. From an information retrieval point of view, this high volume and …

Preprocessing, term selection, term weighting, sentence weighting, and sentence selection
are the main issues in generating extractive summaries of text sentences. Although many …