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 ...

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...

Multi-document summarization is a challenge to information overload problem to provide a condensed text for a number of documents. Most multi-document summarization systems make use of extraction techniques (e.g., important sentence extraction) and compile a summary from the selected information. However, sentences gathered from multiple sources are not organized as a comprehensible text. There...

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...

While most people have a clear idea of what a single document summary should look like, this is not immediately obvious for a multidocument summary. There are many new questions to answer concerning the amount of documents to be summarized, the type of documents, the kind of summary that should be generated, the way the summary gets presented to the user, etc. The many approaches possible to mu...

The update task of multi-document summarization aims at automatically generating the summaries of some event developing with time going. Based on our previous system of multi-document summarization, we summarize the document sets with or without history. In our previous system, the design of features is the important part. Here, in order to adapt to the updating task we introduce a new ‘filteri...