Abstract
XML is rapidly evolving towards the standard for data integration and exchange over the Internet and within intranets, covering the complete spectrum from largely unstructured, ad hoc documents to highly structured, schematic data. However, established XML query languages like XML-QL [96] or XQuery [34] cannot cope with the rapid growth of information in open environments such as the Web or intranets of large corporations, as they are bound to boolean retrieval and do not provide any relevance ranking for the (typically numerous) results. Recent approaches such as XIRQL [128] or our own system XXL [295, 296] that are driven by techniques from information retrieval overcome the latter problem by considering the relevance of each potential hit for the query and returning the results in a ranked order, using similarity measures like the cosine measure. But they are still tied to keyword queries, which is no longer appropriate for highly heterogeneous XML data from different sources, as it is the case in the Web or in large intranets.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Schenkel, R., Theobald, A., Weikum, G. (2003). Ontology-Enabled XML Search. In: Blanken, H., Grabs, T., Schek, HJ., Schenkel, R., Weikum, G. (eds) Intelligent Search on XML Data. Lecture Notes in Computer Science, vol 2818. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45194-5_8
Download citation
DOI: https://doi.org/10.1007/978-3-540-45194-5_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40768-3
Online ISBN: 978-3-540-45194-5
eBook Packages: Springer Book Archive