An adjacency model for sentence ordering in multi-document summarization

被引:0
|
作者
Nie, Yu [1 ]
Ji, Donghong [1 ]
Yang, Lingpeng [1 ]
机构
[1] Inst Infocomm Res, Singapore 119613, Singapore
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we proposed a new method named adjacency based ordering to order sentences for summarization tasks. Given a group of sentences to be organized into the summary, connectivity of each pair of sentences is learned from source documents. Then a top-first strategy is implemented to define the sentence ordering. It provides a solution of ordering texts while other information except the source documents is not available. We compared this method with other existing sentence ordering methods. Experiments and evaluations are made on data collection of DUC04. The results show that this method distinctly outperforms other existing sentence ordering methods. Its low input requirement also makes it capable to most summarization and text generation tasks.
引用
收藏
页码:313 / 322
页数:10
相关论文
共 50 条
  • [41] A Scoring Model Assisted by Frequency for Multi-Document Summarization
    Yu, Yue
    Wu, Mutong
    Su, Weifeng
    Cheung, Yiu-ming
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING, ICANN 2021, PT V, 2021, 12895 : 309 - 320
  • [42] A hybrid machine learning model for multi-document summarization
    Mohamed Abdel Fattah
    Applied Intelligence, 2014, 40 : 592 - 600
  • [43] Assessing shallow sentence scoring techniques and combinations for single and multi-document summarization
    Oliveira, Hilario
    Ferreira, Rafael
    Lima, Rinaldo
    Lins, Rafael Dueire
    Freitas, Fred
    Riss, Marcelo
    Simske, Steven J.
    EXPERT SYSTEMS WITH APPLICATIONS, 2016, 65 : 68 - 86
  • [44] A novel contextual topic model for multi-document summarization
    Yang, Guangbing
    Wen, Dunwei
    Kinshuk
    Chen, Nian-Shing
    Sutinen, Erkki
    EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (03) : 1340 - 1352
  • [45] Multi-document Text Summarization Based on Genetic Algorithm and the Relevance of Sentence Features
    Neri-Mendoza, Veronica
    Ledeneva, Yulia
    Arnulfo Garcia-Hernandez, Rene
    Hernandez-Castaneda, Angel
    PATTERN RECOGNITION, MCPR 2022, 2022, 13264 : 255 - 265
  • [46] A hybrid machine learning model for multi-document summarization
    Fattah, Mohamed Abdel
    APPLIED INTELLIGENCE, 2014, 40 (04) : 592 - 600
  • [47] Multi-document Extractive Summarization Using Window-based Sentence Representation
    Zhang, Yong
    Er, Meng Joo
    Zhao, Rui
    2015 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI), 2015, : 404 - 410
  • [48] A novel Chinese multi-document summarization using clustering based sentence extraction
    Liu, De-Xi
    He, Yan Xiang
    Ji, Dong-Hong
    Yang, Hua
    PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2006, : 2592 - +
  • [49] Single-document and multi-document summarization techniques for email threads using sentence compression
    Zajic, David M.
    Dorr, Bonnie J.
    Lin, Jimmy
    INFORMATION PROCESSING & MANAGEMENT, 2008, 44 (04) : 1600 - 1610
  • [50] INFORMATION ORDERING WITH AN EVENT-ENRICHED VECTOR SPACE MODEL FOR MULTI-DOCUMENT NEWS SUMMARIZATION
    Zhang, Renxian
    Li, Wenjie
    Liu, Naishi
    Lu, Qin
    COMPUTATIONAL INTELLIGENCE, 2016, 32 (02) : 323 - 351