Norbert Fuhr
ABSTRACT
Query languages for retrieval of XML documents allow for conditions referring both to the content and the structure of documents. In this paper, we investigate two different approaches for reducing index space of inverted files for XML documents. First, we consider methods for compressing index entries. Second, we develop the new XS tree data structure which contains the structural description of a document in a rather compact form, such that these descriptions can be kept in main memory. Experimental results on two large XML document collections show that very high compression rates for indexes can be achieved, but any compression increases retrieval time. On the other hand, highly compressed indexes may be feasible for applications where storage is limited, such as in PDAs or E-book devices.
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Digital Library
- N. Fuhr and K. Großjohann. XIRQL: A query language for information retrieval in XML documents. In Proceedings of the SIGIR, pages 172--180, New York, 2001. ACM. Google ScholarDigital Library
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- Alistair Moffat and Justin Zobel. Self-indexing inverted files for fast text retrieval. ACM Transactions on Information Systems, 14(4):349--379, October 1996. Google ScholarDigital Library
- James A. Thom, Justin Zobel, and Bruce Grima. Design of indexes for structured document databases. Technical Report TR-95-8, Collaborative Information Technology Research Institute, Melbourne, Australia, 1995.Google Scholar
- Ian H. Witten, Alistair Moffat, and Timothy~C. Bell. Managing Gigabytes: Compressing and Indexing Documents and Images. Morgan Kaufmann Publishers, 2nd edition, 1999. Google ScholarDigital Library
Index Terms
- Index compression vs. retrieval time of inverted files for XML documents
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