نتایج جستجو برای: multiple document summarization

تعداد نتایج: 904261  

2004
Hiroyuki Sakai Shigeru Masuyama

We propose a multiple-document summa-rization system with user interaction. Our system extracts keywords from sets of documents to be summarized and shows the keywords to a user on the screen. Among them, the user selects some keywords reflecting his/her needs. Our system controls the produced summary by using these selected keywords. For evaluation of our method, we participated in TSC3 of NTC...

2011
Naresh Kumar Nagwani Shrish Verma Alkesh Patel Tanveer Siddiqui U. S. Tiwary George Giannakopoulos Vangelis Karkaletsis George Vouros Massih R. Amini Nicolas Usunier Patrick Gallinari Pradeep Singh René Arnulfo García-Hernández Yulia Ledeneva

Text summarization is an important activity in the analysis of a high volume text documents. Text summarization has number of applications; recently number of applications uses text summarization for the betterment of the text analysis and knowledge representation. In this paper a frequent term based text summarization algorithm is designed and implemented in java. The designed algorithm works ...

1998
Jade Goldstein-Stewart Jaime G. Carbonell

This paper 1 develops a method for combining queryrelevance with information-novelty in the context of text retrieval and summarization. The Maximal Marginal Relevance (MMR) criterion strives to reduce redundancy while maintaining query relevance in reranking retrieved documents and in selecting appropriate passages for text summarization. Preliminary results indicate some benefits for MMR dive...

2009
Ouyang You Wenjie Li

PolyU has participated in both the two tasks in the TAC 2009 summarization track, including the update summarization task and the automatically evaluating summaries of peers (AESOP) task. The update summarization task is to generate short fluent multi-document summaries of news articles. For each topic, a topic statement and two chronologically ordered newswire document sets are given. The task...

2015
He Liu Hongliang Yu Zhi-Hong Deng

Multi-document summarization is of great value to many real world applications since it can help people get the main ideas within a short time. In this paper, we tackle the problem of extracting summary sentences from multi-document sets by applying sparse coding techniques and present a novel framework to this challenging problem. Based on the data reconstruction and sentence denoising assumpt...

Journal: :CoRR 2017
Shashi Narayan Nikos Papasarantopoulos Mirella Lapata Shay B. Cohen

Most extractive summarization methods focus on the main body of the document from which sentences need to be extracted. However, the gist of the document may lie in side information, such as the title and image captions which are often available for newswire articles. We propose to explore side information in the context of single-document extractive summarization. We develop a framework for si...

2016
Gayathri N. Jaisankar

Document summarization deals with providing condensed version of the original document. We present an extractive informative single medical document summarization approach. We compare the tokens in the sentence with cue words. A sentence ranking method is used to extract the important sentences. The existing summarizers are used for performance analysis.

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