By Elisa Bertino, Stavros Christodoulakis, Dimitris Plexousakis, Christophides Vassilis
This e-book constitutes the refereed lawsuits of the ninth foreign convention on Extending Database know-how, EDBT 2004, held in Heraklion, Crete, Greece, in March 2004. The forty two revised complete papers awarded including 2 business software papers, 15 software program demos, and three invited contributions have been conscientiously reviewed and chosen from 294 submissions. The papers are geared up in topical sections on allotted, cellular and peer-to-peer database structures; facts mining and data discovery; reliable database platforms; leading edge question processing options for XML info; facts and data on the net; question processing suggestions for spatial databases; foundations of question processing; complicated question processing and optimization; question processing innovations for info and schemas; multimedia and quality-aware platforms; indexing strategies; and vague series trend queries.
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The service provider) is also responsible for managing the UDDI. By contrast, such standard mechanisms must be revised when a third-party architecture is adopted. The big issue there is how the provider of the services can Security and Privacy for Web Databases and Services 25 ensure security properties to its data, even if the data are managed by a discovery agency. The most intuitive solution is that of requiring the discovery agency to be trusted with respect to the considered security properties.
11. : The XML Security Page. de/ /xml_security. html. 12. : Web Data Mining: Technologies and Their Applications to Business Intelligence and Counter-terrorism (2003), CRC Press. 13. : Privacy Constraint Processing in a Privacy Enhanced Database System, Data and Knowledge Engineering, to appear. 14. : Security Constraint Processing in a Distributed Database Management System, IEEE Transactions on Knowledge and Data Engineering (1995). 15. org. 16. 0, UDDI Spec Technical Committee Specification, July, 19th, 2002.
In particular, each filter should support an efficient filter-match operation such that if a document matches a query then filter-match should also be true. If the filter-match returns false, we say that we have a miss. Definition 2. (filter match) A filter F(D) for a set of documents D has the following property: For any query if then Note that, the reverse does not necessarily hold. That is, if then there may or may not exist documents such that is true. We call false positive the case in which, for a filter F(D) for a set of documents D, but there is no document that satisfies that is We are interested in filters with small probability of false positives.
Advances in Database Technology - EDBT 2004 by Elisa Bertino, Stavros Christodoulakis, Dimitris Plexousakis, Christophides Vassilis