Building semantic information search platform with extended Sesame framework

  • Authors:

  • Tao Chen;Yongjuan Zhang;Shen Zhang;Chengcai Chen;Heng Chen

  • Affiliations:

  • Shanghai Institutes for Biological Sciences/ Shanghai Information Center for Life Sciences, CAS, Shanghai, China;Shanghai Institutes for Biological Sciences/ Shanghai Information Center for Life Sciences, CAS, Shanghai, China;Shanghai Institutes for Biological Sciences/ Shanghai Information Center for Life Sciences, CAS, Shanghai, China;Shanghai Institutes for Biological Sciences/ Shanghai Information Center for Life Sciences, CAS, Shanghai, China;Shanghai Institutes for Biological Sciences/ Shanghai Information Center for Life Sciences, CAS, Shanghai, China

  • Venue:
  • Proceedings of the 8th International Conference on Semantic Systems
  • Year:
  • 2012

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Abstract

Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries. Therefore, this technology can be used to integrate disparate libraries resources in the field of library located in lots of different web sites. Based on Sesame framework, this article aims at building an extended platform which not only be used to convert web pages to RDF, but also provide a common interface to query semantic data among multiple data repositories. System architecture of the extended application is presented firstly, and how to define data and clue extraction rules for collected data from web pages with tools are introduced subsequently. Convert web data to the uniform RDF triple format data is another key point discussed in this paper. How to merge multi-core Solr and SIREn with Sesame system is also an important problem to be solved. Finally, a simple case is also given to prove the solution proposed in this paper. How to publish the linked data of this paper on the web is the advanced task which will be performed in the near future.