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Tag-oriented document summarization

Authors:

Gang LuAuthors Info & Claims

WWW '09: Proceedings of the 18th international conference on World wide web

Pages 1195 - 1196

https://doi.org/10.1145/1526709.1526925

Published: 20 April 2009 Publication History

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Abstract

Social annotations on a Web document are highly generalized description of topics contained in that page. Their tagged frequency indicates the user attentions with various degrees. This makes annotations a good resource for summarizing multiple topics in a Web page. In this paper, we present a tag-oriented Web document summarization approach by using both document content and the tags annotated on that document. To improve summarization performance, a new tag ranking algorithm named EigenTag is proposed in this paper to reduce noise in tags. Meanwhile, association mining technique is employed to expand tag set to tackle the sparsity problem. Experimental results show our tag-oriented summarization has a significant improvement over those not using tags.

References

[1]

P. Heymann, D. Ramage, and H. Garcia-Molina. Social tag prediction. In SIGIR '08.

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[2]

C. Lin. ROUGE: A Package for Automatic Evaluation of Summaries. In WAS '04.

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Cited By

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Alhasan JSulaiman SBarham BHawash A(2022)Automating Arabic Tags Creation for Annotating Web Contents2022 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)10.1109/3ICT56508.2022.9990699(311-318)Online publication date: 20-Nov-2022
https://doi.org/10.1109/3ICT56508.2022.9990699
Jalil ZNasir JNasir M(2021)Extractive Multi-Document Summarization: A Review of Progress in the Last DecadeIEEE Access10.1109/ACCESS.2021.31124969(130928-130946)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3112496
Rinaldi ARusso C(2020)Using a multimedia semantic graph for web document visualization and summarizationMultimedia Tools and Applications10.1007/s11042-020-09761-1Online publication date: 24-Sep-2020
https://doi.org/10.1007/s11042-020-09761-1
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Index Terms

Tag-oriented document summarization
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Document filtering
      2. Information extraction

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Information & Contributors

Information

Published In

WWW '09: Proceedings of the 18th international conference on World wide web

April 2009

1280 pages

ISBN:9781605584874

DOI:10.1145/1526709

General Chairs:
Juan Quemada
DIT-UPM
,
Gonzalo León
DIT-UPM
,
Program Chairs:
Yoelle Maarek
Google Inc., Israel
,
Wolfgang Nejdl
L3S and Hannover University

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 April 2009

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WWW '09

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WWW '09: The 18th International World Wide Web Conference

April 20 - 24, 2009

Madrid, Spain

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Cited By

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Alhasan JSulaiman SBarham BHawash A(2022)Automating Arabic Tags Creation for Annotating Web Contents2022 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)10.1109/3ICT56508.2022.9990699(311-318)Online publication date: 20-Nov-2022
https://doi.org/10.1109/3ICT56508.2022.9990699
Jalil ZNasir JNasir M(2021)Extractive Multi-Document Summarization: A Review of Progress in the Last DecadeIEEE Access10.1109/ACCESS.2021.31124969(130928-130946)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3112496
Rinaldi ARusso C(2020)Using a multimedia semantic graph for web document visualization and summarizationMultimedia Tools and Applications10.1007/s11042-020-09761-1Online publication date: 24-Sep-2020
https://doi.org/10.1007/s11042-020-09761-1
Rinaldi A(2019)Web Summarization and Browsing Through Semantic Tag CloudsInternational Journal of Intelligent Information Technologies10.4018/IJIIT.201907010115:3(1-23)Online publication date: 1-Jul-2019
https://doi.org/10.4018/IJIIT.2019070101
Cagliero LGarza PBaralis E(2019)ELSAACM Transactions on Information Systems10.1145/329898737:2(1-33)Online publication date: 16-Jan-2019
https://dl.acm.org/doi/10.1145/3298987
Liu HWang LZhao PWu X(2019)Document Specific Supervised Keyphrase Extraction With Strong Semantic RelationsIEEE Access10.1109/ACCESS.2019.29488917(167507-167520)Online publication date: 2019
https://doi.org/10.1109/ACCESS.2019.2948891
Rinaldi A(2019)A Document Visualization Strategy Based on Semantic Multimedia Big DataPervasive Systems, Algorithms and Networks10.1007/978-3-030-30143-9_4(43-57)Online publication date: 27-Nov-2019
https://doi.org/10.1007/978-3-030-30143-9_4
Ji SKim YJung SHwang E(2018)An Educational Video Scoring Scheme for Level and Topic-based RecommendationProceedings of the 12th International Conference on Ubiquitous Information Management and Communication10.1145/3164541.3164636(1-5)Online publication date: 5-Jan-2018
https://dl.acm.org/doi/10.1145/3164541.3164636
Cagliero L(2017)Summarization of emergency news articles driven by relevance feedback2017 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2017.8258368(3713-3721)Online publication date: Dec-2017
https://doi.org/10.1109/BigData.2017.8258368
Mohamed A(2016)Automatic summarization of the Arabic documents using NMF: A preliminary study2016 11th International Conference on Computer Engineering & Systems (ICCES)10.1109/ICCES.2016.7822007(235-240)Online publication date: Dec-2016
https://doi.org/10.1109/ICCES.2016.7822007
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Comments-oriented document summarization: understanding documents with readers' feedback

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