Interlinking cross language metadata using heterogeneous graphs and wikipedia

Xiaozhong Liu, Miao Chen, Jian Qin

Research output: Contribution to journalConference Articlepeer-review


Cross-language metadata are essential in helping users overcome language barriers in information discovery and recommendation. The construction of cross-language vocabulary, however, is usually costly and intellectually laborious. This paper addresses these problems by proposing a Cross-Language Metadata Network (CLMN) approach, which uses Wikipedia as the intermediary for cross-language metadata linking. We conducted a proof-of-concept experiment with key metadata in two digital libraries and in two different languages without using machine translation. The experiment result is encouraging and suggests that the CLMN approach has the potential not only to interlink metadata in different languages with reasonable rate of precision and quality but also to construct cross-language metadata vocabulary. Limitations and further research are also discussed.

Original languageEnglish (US)
Pages (from-to)157-166
Number of pages10
JournalProceedings of the International Conference on Dublin Core and Metadata Applications
StatePublished - 2014
Event2014 International Conference on Dublin Core and Metadata Applications, DCMI 2014 - Austin, United States
Duration: Oct 8 2014Oct 11 2014


  • Cross language
  • Heterogeneous graph
  • Linked data
  • Metadata

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Software


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