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Record Linkage for Event Identification in XML Feeds Stream Using ELM

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Proceedings of ELM-2015 Volume 1

Part of the book series: Proceedings in Adaptation, Learning and Optimization ((PALO,volume 6))

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Abstract

Most of the news portals and social media networks are utilizing RSS feeds for information distribution and content sharing. Event identification improves the service quality of feeds providers in the aspect of content distribution and event browsing. However, thriving challenges arise due to representation of structural information and real-time requirement in feeds streams mining. In this paper, we focus on the record linkage problem which classifies stream content into known categories. To realize fast and efficient record linkage over XML feeds stream, we design two classification strategies: a classifier based on ensemble ELMs and an incremental classifier based on OS-ELM. Experimental results show that our solutions provide effective and efficient record linkage for event identification applications.

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Notes

  1. 1.

    http://www.ibm.com/developerworks.

  2. 2.

    http://abcnews.go.com.

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Acknowledgments

This research is partially supported by the National Natural Science Foundation of China under Grant Nos. 61272181, 61173029, and 61173030; the National Basic Research Program of China under Grant No. 2011CB302200-G; the 863 Program under Grant No. 2012AA011004; and the Fundamental Research Funds for the Central Universities under Grant No. N120404006.

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Authors and Affiliations

  1. College of Information Science and Engineering, Northeastern University, Shenyang, 110819, Liaoning, China

    Xin Bi, Xiangguo Zhao, Wenhui Ma, Zhen Zhang & Heng Zhan

Authors
  1. Xin Bi
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  2. Xiangguo Zhao
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  3. Wenhui Ma
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  4. Zhen Zhang
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  5. Heng Zhan
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Corresponding author

Correspondence to Xin Bi .

Editor information

Editors and Affiliations

  1. Institute of Information and Contro, Hangzhou Dianzi University, Zhejiang, China

    Jiuwen Cao

  2. Nanyang Technological University, Singapore, Singapore

    Kezhi Mao

  3. ECE, U of Windsor, WINDSOR, Ontario, Canada

    Jonathan Wu

  4. Dept of Mechanical and Industrial Engg, University of Iowa, Iowa City, Iowa, USA

    Amaury Lendasse

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Bi, X., Zhao, X., Ma, W., Zhang, Z., Zhan, H. (2016). Record Linkage for Event Identification in XML Feeds Stream Using ELM. In: Cao, J., Mao, K., Wu, J., Lendasse, A. (eds) Proceedings of ELM-2015 Volume 1. Proceedings in Adaptation, Learning and Optimization, vol 6. Springer, Cham. https://doi.org/10.1007/978-3-319-28397-5_36

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  • DOI: https://doi.org/10.1007/978-3-319-28397-5_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28396-8

  • Online ISBN: 978-3-319-28397-5

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