XRANK: ranked keyword search over XML documents

  • Authors:

  • Lin Guo;Feng Shao;Chavdar Botev;Jayavel Shanmugasundaram

  • Affiliations:

  • Cornell University;Cornell University;Cornell University;Cornell University

  • Venue:
  • Proceedings of the 2003 ACM SIGMOD international conference on Management of data
  • Year:
  • 2003

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Abstract

We consider the problem of efficiently producing ranked results for keyword search queries over hyperlinked XML documents. Evaluating keyword search queries over hierarchical XML documents, as opposed to (conceptually) flat HTML documents, introduces many new challenges. First, XML keyword search queries do not always return entire documents, but can return deeply nested XML elements that contain the desired keywords. Second, the nested structure of XML implies that the notion of ranking is no longer at the granularity of a document, but at the granularity of an XML element. Finally, the notion of keyword proximity is more complex in the hierarchical XML data model. In this paper, we present the XRANK system that is designed to handle these novel features of XML keyword search. Our experimental results show that XRANK offers both space and performance benefits when compared with existing approaches. An interesting feature of XRANK is that it naturally generalizes a hyperlink based HTML search engine such as Google. XRANK can thus be used to query a mix of HTML and XML documents.