A Universal Model for XML Information Retrieval

نویسندگان

  • Maria Izabel Menezes Azevedo
  • Lucas Pantuza Amorim
  • Nivio Ziviani
چکیده

This paper presents an approach for extending the vector space model (VSM) to perform XML retrieval. The model is extended to support important aspects of XML structural and semantic information such as element nesting level, matching tag names in the query and the collection and the relation between tag names and content of an element. Potential use of the model for heterogeneous as well as for the unstructured collection is also shown. We compared our model with the standard vector space model and obtained a gain for unstructured and structured queries. For unstructured collections the vector space model effectiveness is preserved.

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تاریخ انتشار 2004