Keyword search on structured and semi-structured data

  • Authors:

  • Yi Chen;Wei Wang;Ziyang Liu;Xuemin Lin

  • Affiliations:

  • Arizona State University, Tempe, AZ, USA;University of New South Wales and NICTA, Sydney, Australia;Arizona State University, Tempe, AZ, USA;University of New South Wales and NICTA, Sydney, Australia

  • Venue:
  • Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
  • Year:
  • 2009

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Abstract

Empowering users to access databases using simple keywords can relieve the users from the steep learning curve of mastering a structured query language and understanding complex and possibly fast evolving data schemas. In this tutorial, we give an overview of the state-of-the-art techniques for supporting keyword search on structured and semi-structured data, including query result definition, ranking functions, result generation and top-k query processing, snippet generation, result clustering, query cleaning, performance optimization, and search quality evaluation. Various data models will be discussed, including relational data, XML data, graph-structured data, data streams, and workflows. We also discuss applications that are built upon keyword search, such as keyword based database selection, query generation, and analytical processing. Finally we identify the challenges and opportunities of future research to advance the field.