We present our state of the art multilingual text summarizer capable of single as well as multi-document text summarization. The algorithm is based on repeated application of TextRank on a sentence similarity graph, a bag of words model for sentence similarity and a number of linguistic preand post-processing steps using standard NLP tools. We submitted this algorithm for two different tasks of...

Many of previous research have proven that the usage of rhetorical relations is capable to enhance many applications such as text summarization, question answering and natural language generation. This work proposes an approach that expands the benefit of rhetorical relations to address redundancy problem for cluster-based text summarization of multiple documents. We exploited rhetorical relati...

Text summarization is the process of distilling the most important information from source/sources to produce an abridged version for a particular user/users and task/tasks. Automatically generated summaries can significantly reduce the information overload on intelligence analysts in their daily work. Moreover, automated text summarization can be utilized for automated classification and filte...

With the rapid development of modern technology electronically available textual information has increased to a considerable amount. Summarization of textual information manually from unstructured text sources creates overhead to the user, therefore a systematic approach is required. Summarization is an approach that focuses on providing the user with a condensed version of the original text bu...

Over the past two years we have been developing the text summarization system SUMMARIST. In this paper, we describe the current status of SUMMARIST and its use in TIPSTER Phase III text summarization research.

Sentence compression is a valuable task in the framework of text summarization. In previous works, the sentence is reduced by removing redundant words or phrases from original sentence and tries to remain information. In this paper, we propose a new method that used Grid Model and dynamic programming to calculate n-grams for generating the best sentence compression. These reduced sentences are ...