Text summarization is the process of condensing a long text into a shorter version by
maintaining the key information and its meaning. Automatic text summarization can save …

Multidocument summarization problem deals with extracting main information and ideas
from a set of related documents. Solution to this problem is to find an extraction strategy that …

Automatic text summarization is an exertion of contriving the abridged form of a text
document covering salient knowledge. Numerous statistical, linguistic, rule-based, and …

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 …

Multi-document summarization is used to extract the main ideas of the documents and put
them into a short summary. In multi-document summarization, it is important to reduce …

Since the appearance of text mining, the Arabic language gained some interest in applying
several text mining tasks over a text written in the Arabic language. There are several …

We present an optimization-based unsupervised approach to automatic document
summarization. In the proposed approach, text summarization is modeled as a Boolean …

In this paper, a novel multi-document summarization scheme based on metaheuristic
optimization is introduced that generates a summary by extracting salient and relevant …

This paper proposes a sentence ranking and clustering based summarization method that
extracts essential sentences from a document. To discover central sentences, a weighted …

A method and system for ranking documents of search results based on information richness
and diversity of topics. A ranking system determines the information richness of each …