Automatic patent classification using citation network information: An experimental study in nanotechnology

Xin Li, Hsinchun Chen, Zhu Zhang, Jiexun Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Scopus citations

Abstract

Classifying and organizing documents in repositories is an active research topic in digital library studies. Manually classifying the large volume of patents and patent applications managed by patent offices is a labor-intensive task. Many previous studies have employed patent contents for patent classification with the aim of automating this process. In this research we propose to use patent citation information, especially the citation network structure information, to address the patent classification problem. We adopt a kernel-based approach and design kernel functions to capture content information and various citation-related information in patents. These kernels. performances are evaluated on a testbed of patents related to nanotechnology. Evaluation results show that our proposed labeled citation graph kernel, which utilized citation network structures, significantly outperforms the kernels that use no citation information or only direct citation information.

Original languageEnglish (US)
Title of host publicationProceedings of the 7th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2007
Subtitle of host publicationBuilding and Sustaining the Digital Environment
Pages419-427
Number of pages9
DOIs
StatePublished - Nov 29 2007
Event7th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2007: Building and Sustaining the Digital Environment - Vancouver, BC, Canada
Duration: Jun 18 2007Jun 23 2007

Publication series

NameProceedings of the ACM International Conference on Digital Libraries

Other

Other7th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2007: Building and Sustaining the Digital Environment
CountryCanada
CityVancouver, BC
Period6/18/076/23/07

Keywords

  • Citation network
  • Graph kernel
  • Kernel-based method
  • Machine learning
  • Nanotechnology
  • Patent classification

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

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  • Cite this

    Li, X., Chen, H., Zhang, Z., & Li, J. (2007). Automatic patent classification using citation network information: An experimental study in nanotechnology. In Proceedings of the 7th ACM/IEEE Joint Conference on Digital Libraries, JCDL 2007: Building and Sustaining the Digital Environment (pp. 419-427). (Proceedings of the ACM International Conference on Digital Libraries). https://doi.org/10.1145/1255175.1255262