Copyright 1997 INIST-CNRS CC BY 4.0 Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Sciences of information and communication. Documentation
FRANCIS
Accession Number:
edscal.2484605
Database:
PASCAL Archive
Weitere Informationen
Practical information retrieval systems must manage large volumes of data, often divided into several collections that may be held on separate machines. Techniques for locating matches to queries must therefore consider identification of probable collections as well as identification of documents that are probable answers. Further-more, the large amounts of data involved motivates the use of compression, but in a dynamic environment compression is problematic, because as new text is added the compression model slowly becomes inappropriate. In this paper we describe solutions to both of these problems. We show that use of centralised blocked indexes can reduce overall query processing costs in a multi-collection environment, and that careful application of text compression techniques allow collections to grow by several orders of magnitude without recompression becoming necessary.
