Name
Abstract | ||
|---|---|---|
This paper introduces a model to describe the dynamic evolution of network information, identifying and analyzing the document collection on the same topic in different stages. In order to characterize the dynamic relationship of evolutionary content differences, this paper presents a dynamic multi-document summarization model, which is called the Dynamic Manifold-Ranking Model (DMRM). Some experiments were conducted on the Update Task test data from TAC2008, and results of new model were compared with results from the TAC2008 evaluation. This comparison demonstrated the effectiveness of the model. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/IALP.2011.55 | IALP |
Keywords | Field | DocType |
dynamic relationship,document collection,evolutionary content differences,dynamic network information evolution,dynamic,dynamic manifold-ranking model,dynamic multi-document summarization model,dynamic multidocument summarization model,new model,dynamic manifold ranking model,manifold-ranking,evolutionary content difference,different stage,tac2008 evaluation,dynamic evolution,update task test data,abstracting,text analysis,document collection identification,multi-document summarization model,summarization,document collection analysis,multi document summarization | Multi-document summarization,Data mining,Automatic summarization,Text mining,Information retrieval,Computer science,Test data,Manifold ranking | Conference |
ISBN | Citations | PageRank |
978-1-4577-1733-8 | 0 | 0.34 |
References | Authors | |
4 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Meiling Liu | 1 | 0 | 0.68 |
| Hong-E Ren | 2 | 23 | 4.19 |
| Dequan Zheng | 3 | 74 | 21.56 |
| Tiejun Zhao | 4 | 643 | 102.68 |