Title :
Sentence Descending Algorithm for Automatic Text Summarization
Author :
Zhu, Tiedan ; Liu, Qiongxin
Abstract :
This paper proposes a novel method for automatic text summarization. The topic space model is built through the Chinese Restaurant Process. The documents are mapped to the topic space from vector space. Sentence descending algorithm is introduced to create the summary. An experiment is illustrated on DUC2006 data and the results prove the proposed method effective and well performed.
Keywords :
Algorithm design and analysis; Computational modeling; Extraterrestrial measurements; Mathematical model; Resource management; Semantics; Vectors; Automatic Text Summarization; Chinese Restaurant Process; Sentence descending algorithm; Topic Space Model;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2011 International Conference on
Conference_Location :
Chengdu, China
Print_ISBN :
978-1-4577-1540-2
DOI :
10.1109/ICCIS.2011.249
