GraphSum: Discovering correlations among multiple terms for graph-based summarization
نویسندگان
چکیده
منابع مشابه
GraphSum: Discovering correlations among multiple terms for graph-based summarization
0020-0255/$ see front matter 2013 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ins.2013.06.046 ⇑ Corresponding author. Tel.: +39 0110907084; fax: +39 0110907099. E-mail addresses: [email protected] (E. Baralis), [email protected] (L. Cagliero), [email protected] (N. Mahoto), alessandro.fio (A. Fiori). Elena Baralis , Luca Cagliero a,⇑, Naeem Mahoto , Alessandr...
متن کاملGraph Hybrid Summarization
One solution to process and analysis of massive graphs is summarization. Generating a high quality summary is the main challenge of graph summarization. In the aims of generating a summary with a better quality for a given attributed graph, both structural and attribute similarities must be considered. There are two measures named density and entropy to evaluate the quality of structural and at...
متن کاملGraph-based models for multi-document summarization
University of Ljubljana Faculty of Computer and Information Science Ercan Canhasi Graph-based models for multi-document summarization is thesis is about automatic document summarization, with experimental results on general, query, update and comparative multi-document summarization (MDS). We describe prior work and our own improvements on some important aspects of a summarization system, incl...
متن کاملGraph-Based Marginal Ranking for Update Summarization
Update summarization is to summarize a document collection B given that the users have already read another document collection A, which has time stamp prior to that of B. An important and challenging issue in update summarization is that contents in B already covered by A should be excluded from the update summary. In this paper, we propose a graphbased regularization framework MarginRank for ...
متن کاملTopical Coherence for Graph-based Extractive Summarization
We present an approach for extractive single-document summarization. Our approach is based on a weighted graphical representation of documents obtained by topic modeling. We optimize importance, coherence and non-redundancy simultaneously using ILP. We compare ROUGE scores of our system with state-of-the-art results on scientific articles from PLOS Medicine and on DUC 2002 data. Human judges ev...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Information Sciences
سال: 2013
ISSN: 0020-0255
DOI: 10.1016/j.ins.2013.06.046