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WiiCluster: a Platform for Wikipedia Infobox Generation

Authors:

Wei WangAuthors Info & Claims

CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management

Pages 2033 - 2035

https://doi.org/10.1145/2661829.2661840

Published: 03 November 2014 Publication History

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Abstract

Wikipedia has become one of the best sources for creating and sharing a massive volume of human knowledge. Much effort has been devoted to generating and enriching the structured data by automatic information extraction from unstructured text in Wikipedia. Most, if not all, of the existing work share the same paradigm, that is, starting with information extraction over the unstructured text data, followed by supervised machine learning. Although remarkable progresses have been made, this paradigm has its own limitations in terms of effectiveness, scalability as well as the high labeling cost.

We present WiiCluster, a scalable platform for automatically generating infobox for articles in Wikipedia. The heart of our system is an effective cluster-then-label algorithm over a rich set of semi-structured data in Wikipedia articles: linked entities. It is totally unsupervised and thus does not require any human label. It is effective in generating semantically meaningful summarization for Wikipedia articles. We further propose a cluster-reuse algorithm to scale up our system. Overall, our WiiCluster is able to generate nearly 10 million new facts. We also develop a web-based platform to demonstrate WiiCluster, which enables the users to access and browse the generated knowledge.

References

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G. Hamerly and C. Elkan. Learning the k in k-means. In Proc. of 17th NIPS, 2003.

Google Scholar

[2]

D. P. Nguyen, Y. Matsuo, and M. Ishizuka. Exploiting syntactic and semantic information for relation extraction from wikipedia. IJCAI07-TextLinkWS, 2007.

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A. Sultana, Q. M. Hasan, A. K. Biswas, S. Das, H. Rahman, C. Ding, and C. Li. Infobox suggestion for wikipedia entities. In Proc. of CIKM, 2012.

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[4]

K. Zhang, Y. Xiao, H. Tong, H. Wang, and W. Wang. The links have it: Infobox generation by summarization over linked entities. arXiv:1406.6449, 2014.

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Cited By

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Hättasch BBinnig CChua TNgo CKumar RLauw HKa-Wei Lee R(2024)Box2Go: Collaborative Interactive Infobox FillingCompanion Proceedings of the ACM on Web Conference 202410.1145/3589335.3651235(1003-1006)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589335.3651235
Yadav ARanvijay Yadav RMaurya A(2023)State-of-the-art approach to extractive text summarization: a comprehensive reviewMultimedia Tools and Applications10.1007/s11042-023-14613-982:19(29135-29197)Online publication date: 16-Feb-2023
https://doi.org/10.1007/s11042-023-14613-9
Andhale NBewoor L(2016)An overview of Text Summarization techniques2016 International Conference on Computing Communication Control and automation (ICCUBEA)10.1109/ICCUBEA.2016.7860024(1-7)Online publication date: Aug-2016
https://doi.org/10.1109/ICCUBEA.2016.7860024

Index Terms

WiiCluster: a Platform for Wikipedia Infobox Generation
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
  2. Information systems applications
    1. Data mining
      1. Clustering

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Information

Published In

CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management

November 2014

2152 pages

ISBN:9781450325981

DOI:10.1145/2661829

General Chairs:
Jianzhong Li
Harbin Inst. of Technology
,
X. Sean Wang
Fudan University
,
Program Chairs:
Minos Garofalakis
Technical University of Crete, Greece
,
Ian Soboroff
National Institute of Standards, USA
,
Torsten Suel
New York University, USA
,
Min Wang
Google Research, USA

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 November 2014

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CIKM '14

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CIKM '14: 2014 ACM Conference on Information and Knowledge Management

November 3 - 7, 2014

Shanghai, China

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CIKM '14 Paper Acceptance Rate 175 of 838 submissions, 21%;

Overall Acceptance Rate 1,690 of 7,572 submissions, 22%

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Cited By

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Hättasch BBinnig CChua TNgo CKumar RLauw HKa-Wei Lee R(2024)Box2Go: Collaborative Interactive Infobox FillingCompanion Proceedings of the ACM on Web Conference 202410.1145/3589335.3651235(1003-1006)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589335.3651235
Yadav ARanvijay Yadav RMaurya A(2023)State-of-the-art approach to extractive text summarization: a comprehensive reviewMultimedia Tools and Applications10.1007/s11042-023-14613-982:19(29135-29197)Online publication date: 16-Feb-2023
https://doi.org/10.1007/s11042-023-14613-9
Andhale NBewoor L(2016)An overview of Text Summarization techniques2016 International Conference on Computing Communication Control and automation (ICCUBEA)10.1109/ICCUBEA.2016.7860024(1-7)Online publication date: Aug-2016
https://doi.org/10.1109/ICCUBEA.2016.7860024

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