Efficient decoding of prefix codes
Communications of the ACM
Self-indexing inverted files for fast text retrieval
ACM Transactions on Information Systems (TOIS)
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Managing gigabytes (2nd ed.): compressing and indexing documents and images
XIRQL: a query language for information retrieval in XML documents
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Searching structured documents
Information Processing and Management: an International Journal
A flexible object-oriented system for teaching and learning structured IR
TLIR'07 Proceedings of the First international conference on Teaching and Learning of Information Retrieval
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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.