Mining Query Log to Assist Ontology Learning from Relational Database

  • Jie Zhang
  • Miao Xiong
  • Yong Yu
Conference paper

DOI: 10.1007/11610113_39

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3841)
Cite this paper as:
Zhang J., Xiong M., Yu Y. (2006) Mining Query Log to Assist Ontology Learning from Relational Database. In: Zhou X., Li J., Shen H.T., Kitsuregawa M., Zhang Y. (eds) Frontiers of WWW Research and Development - APWeb 2006. APWeb 2006. Lecture Notes in Computer Science, vol 3841. Springer, Berlin, Heidelberg

Abstract

Ontology learning plays a significant role in migrating legacy knowledge base into the Semantic Web. Relational database is the vital source that stores the structured knowledge today. Some prior work has contributed to the learning process from relational database to ontology. However, a majority of the existing methods focus on the schema dimension, leaving the data dimension not well exploited. In this paper we present a novel approach that exploits the data dimension by mining user query log to glorify the ontology learning process. In addition, we propose a set of rules for schema extraction which serves as the basis of our theme. The presented approach can be applied to a broad range of today’s relational data warehouse.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jie Zhang
    • 1
  • Miao Xiong
    • 1
  • Yong Yu
    • 1
  1. 1.APEX Data and Knowledge Management Lab, Department of Computer Science and EngineeringShanghai JiaoTong UniversityShanghaiP.R. China

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