research-article

TSCAN: a novel method for topic summarization and content anatomy

Authors:

Chien Chin Chen,

Meng Chang ChenAuthors Info & Claims

SIGIR '08: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval

Pages 579 - 586

https://doi.org/10.1145/1390334.1390433

Published: 20 July 2008 Publication History

Abstract

A topic is defined as a seminal event or activity along with all directly related events and activities. It is represented as a chronological sequence of documents by different authors published on the Internet. In this paper, we define a task called topic anatomy, which summarizes and associates core parts of a topic graphically so that readers can understand the content easily. The proposed topic anatomy model, called TSCAN, derives the major themes of a topic from the eigenvectors of a temporal block association matrix. Then, the significant events of the themes and their summaries are extracted by examining the constitution of the eigenvectors. Finally, the extracted events are associated through their temporal closeness and context similarity to form the evolution graph of the topic. Experiments based on the official TDT4 corpus demonstrate that the generated evolution graphs comprehensibly describe the storylines of topics. Moreover, in terms of content coverage and consistency, the produced summaries are superior to those of other summarization methods based on human composed reference summaries.

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Cited By

Keith Norambuena BMitra TNorth C(2023)A Survey on Event-Based News Narrative ExtractionACM Computing Surveys10.1145/358474155:14s(1-39)Online publication date: 17-Jul-2023
https://dl.acm.org/doi/10.1145/3584741
Farzindar AInkpen D(2020)Natural Language Processing for Social Media, Third EditionSynthesis Lectures on Human Language Technologies10.2200/S00999ED3V01Y202003HLT04613:2(1-219)Online publication date: 3-Apr-2020
https://doi.org/10.2200/S00999ED3V01Y202003HLT046
Zhang CJin DXiao XChen GShyu M(2020)A Novel Collaborative Optimization Framework for Web Video Event Mining Based on the Combination of Inaccurate Visual Similarity Detection Information and Sparse Textual InformationIEEE Access10.1109/ACCESS.2020.29647148(10516-10527)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2964714
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Index Terms

TSCAN: a novel method for topic summarization and content anatomy
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources
2. Information systems
  1. Information systems applications
    1. Data mining

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Published In

cover image ACM Conferences

SIGIR '08: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval

July 2008

934 pages

ISBN:9781605581644

DOI:10.1145/1390334

General Chairs:
Tat-Seng Chua
National University of Singapore
,
Mun-Kew Leong
National Library Board, Singapore
,
Program Chairs:
Syung Hyon Myaeng
Information and Communications University, Korea
,
Douglas W. Oard
University of Maryland, College Park, USA
,
Fabrizio Sebastiani
Consiglio Nazionale delle Ricerche, Italy

Copyright © 2008 ACM.

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Publication History

Published: 20 July 2008

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SIGIR '08: The 31st Annual International ACM SIGIR Conference

July 20 - 24, 2008

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Overall Acceptance Rate 792 of 3,983 submissions, 20%

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Cited By

Keith Norambuena BMitra TNorth C(2023)A Survey on Event-Based News Narrative ExtractionACM Computing Surveys10.1145/358474155:14s(1-39)Online publication date: 17-Jul-2023
https://dl.acm.org/doi/10.1145/3584741
Farzindar AInkpen D(2020)Natural Language Processing for Social Media, Third EditionSynthesis Lectures on Human Language Technologies10.2200/S00999ED3V01Y202003HLT04613:2(1-219)Online publication date: 3-Apr-2020
https://doi.org/10.2200/S00999ED3V01Y202003HLT046
Zhang CJin DXiao XChen GShyu M(2020)A Novel Collaborative Optimization Framework for Web Video Event Mining Based on the Combination of Inaccurate Visual Similarity Detection Information and Sparse Textual InformationIEEE Access10.1109/ACCESS.2020.29647148(10516-10527)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2964714
Putri EBuliali JErmawati M(2018)Real-time Detection of Data Completeness Degree for Traffic Simulation Using Text Similarity and Time Relevance of Data from Social Media2018 2nd International Conference on Informatics and Computational Sciences (ICICoS)10.1109/ICICOS.2018.8621644(1-6)Online publication date: Oct-2018
https://doi.org/10.1109/ICICOS.2018.8621644
Goswami AKumar A(2018)Event Detection Using Twitter PlatformDigital Business10.1007/978-3-319-93940-7_18(429-480)Online publication date: 27-Jul-2018
https://doi.org/10.1007/978-3-319-93940-7_18
Farzindar AInkpen D(2017)Natural Language Processing for Social Media, Second EditionSynthesis Lectures on Human Language Technologies10.2200/S00809ED2V01Y201710HLT03810:2(1-195)Online publication date: 15-Dec-2017
https://doi.org/10.2200/S00809ED2V01Y201710HLT038
Sneha SSudarsan D(2017)A novel enhancement to topic summarization using machine legible lexica2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)10.1109/WiSPNET.2017.8299982(1344-1347)Online publication date: Mar-2017
https://doi.org/10.1109/WiSPNET.2017.8299982
Kishore Kumar MKumar S(2017)Temporal summarization for online news articles2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI)10.1109/ICPCSI.2017.8391937(1376-1379)Online publication date: Sep-2017
https://doi.org/10.1109/ICPCSI.2017.8391937
Zhou HYu HHu RHu J(2017)A survey on trends of cross-media topic evolution mapKnowledge-Based Systems10.1016/j.knosys.2017.03.009124:C(164-175)Online publication date: 15-May-2017
https://dl.acm.org/doi/10.1016/j.knosys.2017.03.009
Farzindar A(2016)Social Network Integration in Document SummarizationSocial Media and Networking10.4018/978-1-4666-8614-4.ch096(2102-2125)Online publication date: 2016
https://doi.org/10.4018/978-1-4666-8614-4.ch096
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