TY - GEN
T1 - Generic multi-document summarization using topic-oriented information
AU - Pei, Yulong
AU - Yin, Wenpeng
AU - Huang, Lian'En
PY - 2012
Y1 - 2012
N2 - The graph-based ranking models have been widely used for multi-document summarization recently. By utilizing the correlations between sentences, the salient sentences can be extracted according to the ranking scores. However, sentences are treated in a uniform way without considering the topic-level information in traditional methods. This paper proposes the topic-oriented PageRank (ToPageRank) model, in which topic information is fully incorporated, and the topic-oriented HITS (ToHITS) model is designed to compare the influence of different graph-based algorithms. We choose the DUC2004 data set to examine the models. Experimental results demonstrate the effectiveness of ToPageRank. And the results also show that ToPageRank is more effective and robust than other models including ToHIST under different evaluation metrics.
AB - The graph-based ranking models have been widely used for multi-document summarization recently. By utilizing the correlations between sentences, the salient sentences can be extracted according to the ranking scores. However, sentences are treated in a uniform way without considering the topic-level information in traditional methods. This paper proposes the topic-oriented PageRank (ToPageRank) model, in which topic information is fully incorporated, and the topic-oriented HITS (ToHITS) model is designed to compare the influence of different graph-based algorithms. We choose the DUC2004 data set to examine the models. Experimental results demonstrate the effectiveness of ToPageRank. And the results also show that ToPageRank is more effective and robust than other models including ToHIST under different evaluation metrics.
UR - http://www.scopus.com/inward/record.url?scp=84867681997&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84867681997&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-32695-0_39
DO - 10.1007/978-3-642-32695-0_39
M3 - Conference contribution
AN - SCOPUS:84867681997
SN - 9783642326943
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 435
EP - 446
BT - PRICAI 2012
T2 - 12th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2012
Y2 - 3 September 2012 through 7 September 2012
ER -