The Document Understanding Conference (DUC) 2005 evaluation had a single useroriented, question-focused summarization task, which was to synthesize from a set of 25-50 documents a well-organized, fluent answer to a complex question. The evaluation shows that the best summarization systems have difficulty extracting relevant sentences in response to complex questions (as opposed to representativ...

The technologies for singleand multi-document summarization that are described and evaluated in this article can be used on heterogeneous texts for different summarization tasks. They refer to the extraction of important sentences from the documents, compressing the sentences to their essential or relevant content, and detecting redundant content across sentences. The technologies are tested at...

The rapidly increasing availability of multimedia associated with spoken documents on the Internet has prompted automatic spoken document summarization to be an important research subject. Thus far, the majority of existing work has focused on extractive spoken document summarization, which selects salient sentences from an original spoken document according to a target summarization ratio and ...

The purpose of extractive summarization is to automatically select indicative sentences, passages, or paragraphs from an original document according to a certain target summarization ratio, and then sequence them to form a concise summary. In this paper, in contrast to conventional approaches, our objective is to deal with the extractive summarization problem under a probabilistic modeling fram...

Automatic summarization is the creation of a shortened version of a text by a computer program. The product of this procedure still contains the most important points of the original text. The phenomenon of information overload has meant that access to coherent and correctlydeveloped summaries is vital. In this paper the comparison of the four systems of the automatic summarization is held and ...

The Weibo-oriented Chinese news summarization task aims to automatically generate a short summary for a given Chinese news article, and the short summary is used for news release and propagation on Sina Weibo. The length of the short summary is less than 140 Chinese characters. The task can be considered a special case of single document summarization. In this paper, we will introduce the evalu...

We have developed a multilingual version of Columbia Newsblaster as a testbed for multilingual multi-document summarization. The system collects, clusters, and summarizes news documents from sources all over the world daily. It crawls news sites in many different countries, written in different languages, extracts the news text from the HTML pages, uses a variety of methods to translate the doc...

This paper discusses an approach to topic-oriented multidocument summarization. It investigates the effectiveness of using additional information about the document set as a whole, as well as individual documents. We present NEO-CORTEX, a multi-document summarization system based on the existing CORTEX system. Results are reported for experiments with a document base formed by the NIST DUC-2005...

Preprocessing is a preliminary step in many fields including IR and NLP. The effect of basic preprocessing settings on English for text summarization is well-studied. However, there is no such effort found for the Urdu language (with the best of our knowledge). In this study, we analyze the effect of basic preprocessing settings for single-document text summarization for Urdu, on a benchmark co...

Multi-document summarization represents the information in a concise and comprehensive manner. In this paper we discuss the significance of ordering of sentences in multi document summarization. We show experimental results on DUC2002 dataset. These results show the ordering of summaries before and, improvement in this, after applying sentence ordering. For this purpose we used a term frequency...